ImagesThe future, in bold type
Create a technology article cover with one forceful headline, geometric color bands and a quiet subtitle area.
Creator · JimLiu
Last updated · Sep 7, 2026
Generates article cover images with 5 dimensions (type, palette, rendering, text, mood) combining 11 color palettes and 7 rendering styles. Supports cinematic (2.35:1), widescreen (16:9), and square (1:1) aspects. Use when user asks to "generate cover image", "create article cover", or "make cover".
Published by the site owner
This listing was published directly by the site owner. AI review approval and runtime verification are not implied. Review the source and audit notes before installing.
Creator · JimLiu
Last updated · Sep 7, 2026
Generates article cover images with 5 dimensions (type, palette, rendering, text, mood) combining 11 color palettes and 7 rendering styles. Supports cinematic (2.35:1), widescreen (16:9), and square (1:1) aspects. Use when user asks to "generate cover image", "create article cover", or "make cover".
Published by the site owner
This listing was published directly by the site owner. AI review approval and runtime verification are not implied. Review the source and audit notes before installing.
Creator · JimLiu
Last updated · Sep 7, 2026
Generates article cover images with 5 dimensions (type, palette, rendering, text, mood) combining 11 color palettes and 7 rendering styles. Supports cinematic (2.35:1), widescreen (16:9), and square (1:1) aspects. Use when user asks to "generate cover image", "create article cover", or "make cover".
Published by the site owner
This listing was published directly by the site owner. AI review approval and runtime verification are not implied. Review the source and audit notes before installing.
Creator · JimLiu
Last updated · Sep 7, 2026
Generates article cover images with 5 dimensions (type, palette, rendering, text, mood) combining 11 color palettes and 7 rendering styles. Supports cinematic (2.35:1), widescreen (16:9), and square (1:1) aspects. Use when user asks to "generate cover image", "create article cover", or "make cover".
Published by the site owner
This listing was published directly by the site owner. AI review approval and runtime verification are not implied. Review the source and audit notes before installing.
Owner published · Review required
Install targets
Codex install prompt
Install the "baoyu-cover-image" agent skill from https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-cover-image. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Generates article cover images with 5 dimensions (type, palette, rendering, text, mood) combining 11 color palettes and 7 rendering styles. Supports cinematic (2.35:1), widescreen (16:9), and square (1:1) aspects. Use when user asks to "generate cover image", "create article cover", or "make cover". After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"jimliu-baoyu-skills-baoyu-cover-image","task":"Install baoyu-cover-image","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.See what it makes
ImagesCreate a technology article cover with one forceful headline, geometric color bands and a quiet subtitle area.
ImagesCreate a sustainable-living article cover using flowing landscape contours, organic texture and readable typography.
Supply asset profile
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Scenario
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Agent fit
Claude Code + OpenAI Agents + Cursor
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-cover-image --skill "baoyu-cover-image"
Maintenance
active
2mo since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
26K
80/100 Quality · 82/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · Published by the site owner. Automated review approval and runtime verification are not implied.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Owner published · Review requiredPublished by the site owner. Automated review approval and runtime verification are not implied.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Review the pinned source before installing.
Stars
26K GitHub stars
Repo activity
26K stars, 2.9K forks
Maintenance
2mo since push
License
MIT
Install
npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-cover-image --skill "baoyu-cover-image"
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-cover-image --skill "baoyu-cover-image"Do not use when
Alternative
40.4K Stars
npx skills add PatrickJS/awesome-cursorrules
Alternative
246.3K Stars
npx skills add affaan-m/ECC --skill agent-introspection-debugging
Alternative
3.1K Stars
npx skills add humanlayer/skills --skill narrow-react-prop-types
Alternative
639 Stars
npx skills add sandbaseai/sandbase-harness --skill code-review
Agent safety v2
Published by the site owner. Automated review approval and runtime verification are not implied.
Inspect the pinned source and approve installation explicitly in an isolated workspace.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20baoyu-cover-image%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20baoyu-cover-image%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/jimliu-baoyu-skills-baoyu-cover-image/install
Agent should check
Copy prompt
Task: Use baoyu-cover-image in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20baoyu-cover-image%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/jimliu-baoyu-skills-baoyu-cover-image/install
Install command: npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-cover-image --skill "baoyu-cover-image"
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/jimliu-baoyu-skills-baoyu-cover-image/install
LLM text format
/api/skills/jimliu-baoyu-skills-baoyu-cover-image/install?format=text
Find alternatives
/api/skills/search?q=baoyu-cover-image&limit=3
Agent prompt
Use baoyu-cover-image for this task. Review https://www.openagentskill.com/api/skills/jimliu-baoyu-skills-baoyu-cover-image/install, then install with: npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-cover-image --skill "baoyu-cover-image"Registry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/jimliu-baoyu-skills-baoyu-cover-image
LLM text
/api/registry/manifest/jimliu-baoyu-skills-baoyu-cover-image?format=text
Install alias
/api/registry/install/jimliu-baoyu-skills-baoyu-cover-image
Recommend
/api/registry/recommend?task=Use%20baoyu-cover-image%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code, OpenAI Agents, Cursor
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Published by the site owner. Automated review approval and runtime verification are not implied.
Role in stack
Needs validation
Primary fit
Research agents
Trust label
Needs manual review
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Published by the site owner. Automated review approval and runtime verification are not implied.
GitHub adoption
PASS26K GitHub stars
Stars/forks activity
PASS26K stars, 2.9K forks; issue activity unavailable in current metadata
Recent maintenance
PASS2mo since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Review the pinned source before installing.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Parse messy files
I need my agent to read PDFs, extract tables, and turn documents into structured data.
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Workflow fit
Inspect, patch, and verify code
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Alternative shortlist
Similar skills that may fit this task.
A curated collection of cursor rules for various frameworks and technologies
Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.
narrow React component prop types to match live code paths
Reviews a supplied code path or diff for correctness, security, maintainability, and style without executing or modifying it
--- name: baoyu-cover-image description: Generates article cover images with 5 dimensions (type, palette, rendering, text, mood) combining 11 color palettes and 7 rendering styles. Supports cinematic (2.35:1), widescreen (16:9), and square (1:1) aspects. Use when user asks to "generate cover image", "create article cover", or "make cover". version: 1.117.5 metadata: openclaw: homepage: https://github.com/JimLiu/baoyu-skills#baoyu-cover-image ---
# Cover Image Generator
Generate elegant cover images for articles with 5-dimensional customization.
## User Input Tools
When this skill prompts the user, follow this tool-selection rule (priority order):
1. **Prefer built-in user-input tools** exposed by the current agent runtime — e.g., `AskUserQuestion`, `request_user_input`, `clarify`, `ask_user`, or any equivalent. 2. **Fallback**: if no such tool exists, emit a numbered plain-text message and ask the user to reply with the chosen number/answer for each question. 3. **Batching**: if the tool supports multiple questions per call, combine all applicable questions into a single call; if only single-question, ask them one at a time in priority order.
Concrete `AskUserQuestion` references below are examples — substitute the local equivalent in other runtimes.
## Image Generation Tools
When this skill needs to render an image, resolve the backend in this order:
1. **Current-request override** — if the user names a specific backend in the current message, use it. 2. **Saved preference** — if `EXTEND.md` sets `preferred_image_backend` to a backend available right now, use it. 3. **Auto-select** (when the preference is `auto`, unset, or the pinned backend isn't available): - **Codex (`imagegen`)** — first, inspect your available-skills / tool inventory. If a skill named `imagegen` is listed, you are running inside Codex and MUST use it: invoke via the `Skill` tool with `skill: "imagegen"`, passing the saved prompt file's content (plus output path and aspect ratio per Codex `imagegen`'s own args). Codex `imagegen` is the official raster backend in that runtime and outranks any non-native skill (e.g., `baoyu-image-gen`) unless the user has explicitly pinned a different `preferred_image_backend`. - **Codex via `codex exec` (`codex-imagegen`)** — if the current runtime exposes no native `imagegen` skill but the `codex` CLI is on `PATH` with an active `codex login`, route through `baoyu-image-gen --provider codex-cli` (preferred), or — if baoyu-image-gen is unavailable — invoke the bundled wrapper directly. Details, parameters, and the runtime-discovery procedure live in [references/codex-imagegen.md](references/codex-imagegen.md) — load that file only when this branch is selected. - **Cursor (`GenerateImage`)** — if the runtime exposes a native `GenerateImage` tool, you are running inside Cursor and it outranks any non-native skill the same way Codex `imagegen` does. Two hard caveats: (a) it has no aspect-ratio parameter — state the target aspect ratio / dimensions explicitly in the prompt text passed as `description`; (b) it does not accept an output directory — it saves to a tool-managed location, so after generation copy/move the file to the skill's expected output path (e.g., `outputs/.../NN-xxx.png`). Reference images go in `reference_image_paths`. - **Other runtime-native tools** — if the runtime exposes a different native image tool (e.g., Hermes `image_generate`), use it the same way. - Otherwise, if exactly one non-native backend is installed (e.g., `baoyu-image-gen`), use it. - Otherwise (multiple non-native backends with no runtime-native tool), ask the user once — batch with any other initial questions. 4. **If none are available**, tell the user and ask how to proceed.
**⛔ Never substitute SVG, HTML, canvas, or other code-based rendering for raster image generation.** Codex `imagegen`'s own description says it should be used "when the output should be a bitmap asset rather than repo-native code or vector." If you cannot resolve a raster backend via step 3, fall through to step 4 and ask the user — do **not** silently emit SVG, write inline `<svg>` markup, or produce HTML/CSS art as a substitute. This applies even if the article/section seems "diagram-like": the consumer skill calling this rule has already decided that a raster image is what it needs.
**⛔ Never repair rendered text by painting over a generated bitmap.** Do not use ImageMagick, Pillow, Canvas, SVG, HTML/CSS, OCR scripts, or any other programmatic overlay to cover, rewrite, erase, stroke, or replace title/subtitle text inside an already generated cover image. If text is wrong or unclear, regenerate from a corrected prompt, switch to a lower-text or no-title variant, or ask the user which imperfect candidate to keep.
Setting `preferred_image_backend: ask` forces the step-3 prompt every run regardless of available backends. Users change the pinned backend via the `## Changing Preferences` section below.
**Prompt file requirement (hard)**: write each image's full, final prompt to a standalone file under `prompts/` (naming: `NN-{type}-[slug].md`) BEFORE invoking any backend. The backend receives the prompt file (or its content); the file is the reproducibility record and lets you switch backends without regenerating prompts.
Concrete tool names (`imagegen`, `GenerateImage`, `image_generate`, `baoyu-image-gen`) above are examples — substitute the local equivalents under the same rule.
## Confirmation Policy
Default behavior: **confirm before generation**.
- Treat explicit skill invocation, a file path, matched keywords/presets, `EXTEND.md` defaults, and any documented auto-selection as **recommendation inputs only**. None of them authorizes skipping confirmation. - Do **not** start Step 3 or Step 4 until the user confirms the dimensions / aspect / language / backend choices. - Skip confirmation only when the current request explicitly says to do so, for example: `--quick`, "直接生成", "不用确认", "跳过确认", "按默认出图", or equivalent wording. `quick_mode: true` in `EXTEND.md` counts as a standing explicit opt-out — set it only when you want every run to skip Step 2. - If confirmation is skipped explicitly, state the assumed dimensions / aspect / language / backend in the next user-facing update before generating.
## Options
| Option | Description | |--------|-------------| | `--type <name>` | hero, conceptual, typography, metaphor, scene, minimal | | `--palette <name>` | warm, elegant, cool, dark, earth, vivid, pastel, mono, retro, duotone, macaron | | `--rendering <name>` | flat-vector, hand-drawn, painterly, digital, pixel, chalk, screen-print | | `--style <name>` | Preset shorthand (see [Style Presets](references/style-presets.md)) | | `--text <level>` | none, title-only, title-subtitle, text-rich | | `--mood <level>` | subtle, balanced, bold | | `--font <name>` | clean, handwritten, serif, display | | `--aspect <ratio>` | 16:9 (default), 2.35:1, 4:3, 3:2, 1:1, 3:4 | | `--lang <code>` | Title language (en, zh, ja, etc.) | | `--no-title` | Alias for `--text none` | | `--quick` | Skip confirmation, use auto-selection | | `--ref <files...>` | Reference images for style/composition guidance |
## Five Dimensions
| Dimension | Values | Default | |-----------|--------|---------| | **Type** | hero, conceptual, typography, metaphor, scene, minimal | auto | | **Palette** | warm, elegant, cool, dark, earth, vivid, pastel, mono, retro, duotone, macaron | auto | | **Rendering** | flat-vector, hand-drawn, painterly, digital, pixel, chalk, screen-print | auto | | **Text** | none, title-only, title-subtitle, text-rich | title-only | | **Mood** | subtle, balanced, bold | balanced | | **Font** | clean, handwritten, serif, display | clean |
Auto-selection rules: [references/auto-selection.md](references/auto-selection.md)
## Galleries
**Types**: hero, conceptual, typography, metaphor, scene, minimal → Details: [references/types.md](references/types.md)
**Palettes**: warm, elegant, cool, dark, earth, vivid, pastel, mono, retro, duotone, macaron → Details: [references/palettes/](references/palettes/)
**Renderings**: flat-vector, hand-drawn, painterly, digital, pixel, chalk, screen-print → Details: [references/renderings/](references/renderings/)
**Text Levels**: none (pure visual) | title-only (default) | title-subtitle | text-rich (with tags) → Details: [references/dimensions/text.md](references/dimensions/text.md)
**Mood Levels**: subtle (low contrast) | balanced (default) | bold (high contrast) → Details: [references/dimensions/mood.md](references/dimensions/mood.md)
**Fonts**: clean (sans-serif) | handwritten | serif | display (bold decorative) → Details: [references/dimensions/font.md](references/dimensions/font.md)
## File Structure
Output directory per `default_output_dir` preference: - `same-dir`: `{article-dir}/` - `imgs-subdir`: `{article-dir}/imgs/` - `independent` (default): `cover-image/{topic-slug}/`
``` <output-dir>/ ├── source-{slug}.{ext} # Source files ├── refs/ # Reference images (if provided) │ ├── ref-01-{slug}.{ext} │ └── ref-01-{slug}.md # Description file ├── prompts/cover.md # Generation prompt └── cover.png # Output image ```
**Slug**: 2-4 words, kebab-case. Conflict: append `-YYYYMMDD-HHMMSS`
## Workflow
### Progress Checklist
``` Cover Image Progress: - [ ] Step 0: Check preferences (EXTEND.md) ⛔ BLOCKING - [ ] Step 1: Analyze content + save refs + determine output dir - [ ] Step 2: Confirm options (6 dimensions) ⚠️ unless --quick - [ ] Step 3: Create prompt - [ ] Step 4: Generate image - [ ] Step 5: Completion report ```
### Flow
``` Input → [Step 0: Preferences] ─┬─ Found → Continue └─ Not found → First-Time Setup ⛔ BLOCKING → Save EXTEND.md → Continue ↓ Analyze + Save Refs → [Output Dir] → [Confirm: 6 Dimensions] → Prompt → Generate → Complete ↓ (skip if --quick or all specified) ```
### Step 0: Load Preferences ⛔ BLOCKING
Check EXTEND.md in priority order — the first one found wins:
| Priority | Path | Scope | |----------|------|-------| | 1 | `.baoyu-skills/baoyu-cover-image/EXTEND.md` | Project | | 2 | `${XDG_CONFIG_HOME:-$HOME/.config}/baoyu-skills/baoyu-cover-image/EXTEND.md` | XDG | | 3 | `$HOME/.baoyu-skills/baoyu-cover-image/EXTEND.md` | User home |
| Result | Action | |--------|--------| | Found | Load, display summary → Continue | | Not found | ⛔ Run first-time setup ([references/config/first-time-setup.md](references/config/first-time-setup.md)) → Save → Continue |
**CRITICAL**: If not found, complete setup BEFORE any other steps or questions.
### Step 1: Analyze Content
1. **Save reference images** (if provided) → [references/workflow/reference-images.md](references/workflow/reference-images.md) 2. **Save source content** (if pasted, save to `source.md`) 3. **Analyze content**: topic, tone, keywords, visual metaphors 4. **Deep analyze references** ⚠️: Extract specific, concrete elements (see reference-images.md) 5. **Detect language**: Compare source, user input, EXTEND.md preference 6. **Determine output directory**: Per File Structure rules
**⚠️ People in Reference Images:**
If reference images contain **people** who should appear in the cover:
- **Model supports `--ref`** (default): Copy image to `refs/`, pass via `--ref` at generation. No description file needed — the model sees the face directly. - **Model does NOT support `--ref`** (Jimeng, Seedream 3.0): Create `refs/ref-NN-{slug}.md` with per-character description (hair, glasses, skin tone, clothing). Embed as MUST/REQUIRED instructions in prompt text.
See [reference-images.md](references/workflow/reference-images.md) for full decision table.
### Step 2: Confirm Options ⚠️
**Hard gate**: this step is mandatory per the [Confirmation Policy](#confirmation-policy) — Steps 3–4 cannot start until the user confirms
Source provenance
Decision snapshot
25,722 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for baoyu-cover-image, ready for a manual X post.
baoyu-cover-image: Generates article cover images with 5 dimensions (type, palette, rendering, text, mood) combi... 25.7K stars https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-cover-image?ref=x
Listing + install path for baoyu-cover-image: https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-cover-image?ref=x Install: npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0...
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
This Registry indexed listing is attributed to JimLiu but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-cover-image?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-cover-image?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-cover-image/audit)
[](https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-cover-image?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)JimLiu
@jimliu
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Owner published · Review required
Cursor Rules
A curated collection of cursor rules for various frameworks and technologies
40.4K Starsagent-introspection-debugging
Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.
246.3K Starsnarrow-react-prop-types
narrow React component prop types to match live code paths
3.1K Starscode-review
Reviews a supplied code path or diff for correctness, security, maintainability, and style without executing or modifying it
639 StarsOwner published · Review required
Install targets
Codex install prompt
Install the "baoyu-cover-image" agent skill from https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-cover-image. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Generates article cover images with 5 dimensions (type, palette, rendering, text, mood) combining 11 color palettes and 7 rendering styles. Supports cinematic (2.35:1), widescreen (16:9), and square (1:1) aspects. Use when user asks to "generate cover image", "create article cover", or "make cover". After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"jimliu-baoyu-skills-baoyu-cover-image","task":"Install baoyu-cover-image","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.See what it makes
ImagesCreate a technology article cover with one forceful headline, geometric color bands and a quiet subtitle area.
ImagesCreate a sustainable-living article cover using flowing landscape contours, organic texture and readable typography.
Supply asset profile
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Scenario
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Agent fit
Claude Code + OpenAI Agents + Cursor
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-cover-image --skill "baoyu-cover-image"
Maintenance
active
2mo since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
26K
80/100 Quality · 82/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · Published by the site owner. Automated review approval and runtime verification are not implied.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Owner published · Review requiredPublished by the site owner. Automated review approval and runtime verification are not implied.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Review the pinned source before installing.
Stars
26K GitHub stars
Repo activity
26K stars, 2.9K forks
Maintenance
2mo since push
License
MIT
Install
npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-cover-image --skill "baoyu-cover-image"
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-cover-image --skill "baoyu-cover-image"Do not use when
Alternative
40.4K Stars
npx skills add PatrickJS/awesome-cursorrules
Alternative
246.3K Stars
npx skills add affaan-m/ECC --skill agent-introspection-debugging
Alternative
3.1K Stars
npx skills add humanlayer/skills --skill narrow-react-prop-types
Alternative
639 Stars
npx skills add sandbaseai/sandbase-harness --skill code-review
Agent safety v2
Published by the site owner. Automated review approval and runtime verification are not implied.
Inspect the pinned source and approve installation explicitly in an isolated workspace.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20baoyu-cover-image%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20baoyu-cover-image%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/jimliu-baoyu-skills-baoyu-cover-image/install
Agent should check
Copy prompt
Task: Use baoyu-cover-image in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20baoyu-cover-image%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/jimliu-baoyu-skills-baoyu-cover-image/install
Install command: npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-cover-image --skill "baoyu-cover-image"
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/jimliu-baoyu-skills-baoyu-cover-image/install
LLM text format
/api/skills/jimliu-baoyu-skills-baoyu-cover-image/install?format=text
Find alternatives
/api/skills/search?q=baoyu-cover-image&limit=3
Agent prompt
Use baoyu-cover-image for this task. Review https://www.openagentskill.com/api/skills/jimliu-baoyu-skills-baoyu-cover-image/install, then install with: npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-cover-image --skill "baoyu-cover-image"Registry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/jimliu-baoyu-skills-baoyu-cover-image
LLM text
/api/registry/manifest/jimliu-baoyu-skills-baoyu-cover-image?format=text
Install alias
/api/registry/install/jimliu-baoyu-skills-baoyu-cover-image
Recommend
/api/registry/recommend?task=Use%20baoyu-cover-image%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code, OpenAI Agents, Cursor
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Published by the site owner. Automated review approval and runtime verification are not implied.
Role in stack
Needs validation
Primary fit
Research agents
Trust label
Needs manual review
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Published by the site owner. Automated review approval and runtime verification are not implied.
GitHub adoption
PASS26K GitHub stars
Stars/forks activity
PASS26K stars, 2.9K forks; issue activity unavailable in current metadata
Recent maintenance
PASS2mo since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Review the pinned source before installing.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Parse messy files
I need my agent to read PDFs, extract tables, and turn documents into structured data.
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Workflow fit
Inspect, patch, and verify code
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Alternative shortlist
Similar skills that may fit this task.
A curated collection of cursor rules for various frameworks and technologies
Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.
narrow React component prop types to match live code paths
Reviews a supplied code path or diff for correctness, security, maintainability, and style without executing or modifying it
--- name: baoyu-cover-image description: Generates article cover images with 5 dimensions (type, palette, rendering, text, mood) combining 11 color palettes and 7 rendering styles. Supports cinematic (2.35:1), widescreen (16:9), and square (1:1) aspects. Use when user asks to "generate cover image", "create article cover", or "make cover". version: 1.117.5 metadata: openclaw: homepage: https://github.com/JimLiu/baoyu-skills#baoyu-cover-image ---
# Cover Image Generator
Generate elegant cover images for articles with 5-dimensional customization.
## User Input Tools
When this skill prompts the user, follow this tool-selection rule (priority order):
1. **Prefer built-in user-input tools** exposed by the current agent runtime — e.g., `AskUserQuestion`, `request_user_input`, `clarify`, `ask_user`, or any equivalent. 2. **Fallback**: if no such tool exists, emit a numbered plain-text message and ask the user to reply with the chosen number/answer for each question. 3. **Batching**: if the tool supports multiple questions per call, combine all applicable questions into a single call; if only single-question, ask them one at a time in priority order.
Concrete `AskUserQuestion` references below are examples — substitute the local equivalent in other runtimes.
## Image Generation Tools
When this skill needs to render an image, resolve the backend in this order:
1. **Current-request override** — if the user names a specific backend in the current message, use it. 2. **Saved preference** — if `EXTEND.md` sets `preferred_image_backend` to a backend available right now, use it. 3. **Auto-select** (when the preference is `auto`, unset, or the pinned backend isn't available): - **Codex (`imagegen`)** — first, inspect your available-skills / tool inventory. If a skill named `imagegen` is listed, you are running inside Codex and MUST use it: invoke via the `Skill` tool with `skill: "imagegen"`, passing the saved prompt file's content (plus output path and aspect ratio per Codex `imagegen`'s own args). Codex `imagegen` is the official raster backend in that runtime and outranks any non-native skill (e.g., `baoyu-image-gen`) unless the user has explicitly pinned a different `preferred_image_backend`. - **Codex via `codex exec` (`codex-imagegen`)** — if the current runtime exposes no native `imagegen` skill but the `codex` CLI is on `PATH` with an active `codex login`, route through `baoyu-image-gen --provider codex-cli` (preferred), or — if baoyu-image-gen is unavailable — invoke the bundled wrapper directly. Details, parameters, and the runtime-discovery procedure live in [references/codex-imagegen.md](references/codex-imagegen.md) — load that file only when this branch is selected. - **Cursor (`GenerateImage`)** — if the runtime exposes a native `GenerateImage` tool, you are running inside Cursor and it outranks any non-native skill the same way Codex `imagegen` does. Two hard caveats: (a) it has no aspect-ratio parameter — state the target aspect ratio / dimensions explicitly in the prompt text passed as `description`; (b) it does not accept an output directory — it saves to a tool-managed location, so after generation copy/move the file to the skill's expected output path (e.g., `outputs/.../NN-xxx.png`). Reference images go in `reference_image_paths`. - **Other runtime-native tools** — if the runtime exposes a different native image tool (e.g., Hermes `image_generate`), use it the same way. - Otherwise, if exactly one non-native backend is installed (e.g., `baoyu-image-gen`), use it. - Otherwise (multiple non-native backends with no runtime-native tool), ask the user once — batch with any other initial questions. 4. **If none are available**, tell the user and ask how to proceed.
**⛔ Never substitute SVG, HTML, canvas, or other code-based rendering for raster image generation.** Codex `imagegen`'s own description says it should be used "when the output should be a bitmap asset rather than repo-native code or vector." If you cannot resolve a raster backend via step 3, fall through to step 4 and ask the user — do **not** silently emit SVG, write inline `<svg>` markup, or produce HTML/CSS art as a substitute. This applies even if the article/section seems "diagram-like": the consumer skill calling this rule has already decided that a raster image is what it needs.
**⛔ Never repair rendered text by painting over a generated bitmap.** Do not use ImageMagick, Pillow, Canvas, SVG, HTML/CSS, OCR scripts, or any other programmatic overlay to cover, rewrite, erase, stroke, or replace title/subtitle text inside an already generated cover image. If text is wrong or unclear, regenerate from a corrected prompt, switch to a lower-text or no-title variant, or ask the user which imperfect candidate to keep.
Setting `preferred_image_backend: ask` forces the step-3 prompt every run regardless of available backends. Users change the pinned backend via the `## Changing Preferences` section below.
**Prompt file requirement (hard)**: write each image's full, final prompt to a standalone file under `prompts/` (naming: `NN-{type}-[slug].md`) BEFORE invoking any backend. The backend receives the prompt file (or its content); the file is the reproducibility record and lets you switch backends without regenerating prompts.
Concrete tool names (`imagegen`, `GenerateImage`, `image_generate`, `baoyu-image-gen`) above are examples — substitute the local equivalents under the same rule.
## Confirmation Policy
Default behavior: **confirm before generation**.
- Treat explicit skill invocation, a file path, matched keywords/presets, `EXTEND.md` defaults, and any documented auto-selection as **recommendation inputs only**. None of them authorizes skipping confirmation. - Do **not** start Step 3 or Step 4 until the user confirms the dimensions / aspect / language / backend choices. - Skip confirmation only when the current request explicitly says to do so, for example: `--quick`, "直接生成", "不用确认", "跳过确认", "按默认出图", or equivalent wording. `quick_mode: true` in `EXTEND.md` counts as a standing explicit opt-out — set it only when you want every run to skip Step 2. - If confirmation is skipped explicitly, state the assumed dimensions / aspect / language / backend in the next user-facing update before generating.
## Options
| Option | Description | |--------|-------------| | `--type <name>` | hero, conceptual, typography, metaphor, scene, minimal | | `--palette <name>` | warm, elegant, cool, dark, earth, vivid, pastel, mono, retro, duotone, macaron | | `--rendering <name>` | flat-vector, hand-drawn, painterly, digital, pixel, chalk, screen-print | | `--style <name>` | Preset shorthand (see [Style Presets](references/style-presets.md)) | | `--text <level>` | none, title-only, title-subtitle, text-rich | | `--mood <level>` | subtle, balanced, bold | | `--font <name>` | clean, handwritten, serif, display | | `--aspect <ratio>` | 16:9 (default), 2.35:1, 4:3, 3:2, 1:1, 3:4 | | `--lang <code>` | Title language (en, zh, ja, etc.) | | `--no-title` | Alias for `--text none` | | `--quick` | Skip confirmation, use auto-selection | | `--ref <files...>` | Reference images for style/composition guidance |
## Five Dimensions
| Dimension | Values | Default | |-----------|--------|---------| | **Type** | hero, conceptual, typography, metaphor, scene, minimal | auto | | **Palette** | warm, elegant, cool, dark, earth, vivid, pastel, mono, retro, duotone, macaron | auto | | **Rendering** | flat-vector, hand-drawn, painterly, digital, pixel, chalk, screen-print | auto | | **Text** | none, title-only, title-subtitle, text-rich | title-only | | **Mood** | subtle, balanced, bold | balanced | | **Font** | clean, handwritten, serif, display | clean |
Auto-selection rules: [references/auto-selection.md](references/auto-selection.md)
## Galleries
**Types**: hero, conceptual, typography, metaphor, scene, minimal → Details: [references/types.md](references/types.md)
**Palettes**: warm, elegant, cool, dark, earth, vivid, pastel, mono, retro, duotone, macaron → Details: [references/palettes/](references/palettes/)
**Renderings**: flat-vector, hand-drawn, painterly, digital, pixel, chalk, screen-print → Details: [references/renderings/](references/renderings/)
**Text Levels**: none (pure visual) | title-only (default) | title-subtitle | text-rich (with tags) → Details: [references/dimensions/text.md](references/dimensions/text.md)
**Mood Levels**: subtle (low contrast) | balanced (default) | bold (high contrast) → Details: [references/dimensions/mood.md](references/dimensions/mood.md)
**Fonts**: clean (sans-serif) | handwritten | serif | display (bold decorative) → Details: [references/dimensions/font.md](references/dimensions/font.md)
## File Structure
Output directory per `default_output_dir` preference: - `same-dir`: `{article-dir}/` - `imgs-subdir`: `{article-dir}/imgs/` - `independent` (default): `cover-image/{topic-slug}/`
``` <output-dir>/ ├── source-{slug}.{ext} # Source files ├── refs/ # Reference images (if provided) │ ├── ref-01-{slug}.{ext} │ └── ref-01-{slug}.md # Description file ├── prompts/cover.md # Generation prompt └── cover.png # Output image ```
**Slug**: 2-4 words, kebab-case. Conflict: append `-YYYYMMDD-HHMMSS`
## Workflow
### Progress Checklist
``` Cover Image Progress: - [ ] Step 0: Check preferences (EXTEND.md) ⛔ BLOCKING - [ ] Step 1: Analyze content + save refs + determine output dir - [ ] Step 2: Confirm options (6 dimensions) ⚠️ unless --quick - [ ] Step 3: Create prompt - [ ] Step 4: Generate image - [ ] Step 5: Completion report ```
### Flow
``` Input → [Step 0: Preferences] ─┬─ Found → Continue └─ Not found → First-Time Setup ⛔ BLOCKING → Save EXTEND.md → Continue ↓ Analyze + Save Refs → [Output Dir] → [Confirm: 6 Dimensions] → Prompt → Generate → Complete ↓ (skip if --quick or all specified) ```
### Step 0: Load Preferences ⛔ BLOCKING
Check EXTEND.md in priority order — the first one found wins:
| Priority | Path | Scope | |----------|------|-------| | 1 | `.baoyu-skills/baoyu-cover-image/EXTEND.md` | Project | | 2 | `${XDG_CONFIG_HOME:-$HOME/.config}/baoyu-skills/baoyu-cover-image/EXTEND.md` | XDG | | 3 | `$HOME/.baoyu-skills/baoyu-cover-image/EXTEND.md` | User home |
| Result | Action | |--------|--------| | Found | Load, display summary → Continue | | Not found | ⛔ Run first-time setup ([references/config/first-time-setup.md](references/config/first-time-setup.md)) → Save → Continue |
**CRITICAL**: If not found, complete setup BEFORE any other steps or questions.
### Step 1: Analyze Content
1. **Save reference images** (if provided) → [references/workflow/reference-images.md](references/workflow/reference-images.md) 2. **Save source content** (if pasted, save to `source.md`) 3. **Analyze content**: topic, tone, keywords, visual metaphors 4. **Deep analyze references** ⚠️: Extract specific, concrete elements (see reference-images.md) 5. **Detect language**: Compare source, user input, EXTEND.md preference 6. **Determine output directory**: Per File Structure rules
**⚠️ People in Reference Images:**
If reference images contain **people** who should appear in the cover:
- **Model supports `--ref`** (default): Copy image to `refs/`, pass via `--ref` at generation. No description file needed — the model sees the face directly. - **Model does NOT support `--ref`** (Jimeng, Seedream 3.0): Create `refs/ref-NN-{slug}.md` with per-character description (hair, glasses, skin tone, clothing). Embed as MUST/REQUIRED instructions in prompt text.
See [reference-images.md](references/workflow/reference-images.md) for full decision table.
### Step 2: Confirm Options ⚠️
**Hard gate**: this step is mandatory per the [Confirmation Policy](#confirmation-policy) — Steps 3–4 cannot start until the user confirms
Source provenance
Decision snapshot
25,722 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for baoyu-cover-image, ready for a manual X post.
baoyu-cover-image: Generates article cover images with 5 dimensions (type, palette, rendering, text, mood) combi... 25.7K stars https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-cover-image?ref=x
Listing + install path for baoyu-cover-image: https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-cover-image?ref=x Install: npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0...
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
This Registry indexed listing is attributed to JimLiu but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-cover-image?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-cover-image?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-cover-image/audit)
[](https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-cover-image?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)JimLiu
@jimliu
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Owner published · Review required
Cursor Rules
A curated collection of cursor rules for various frameworks and technologies
40.4K Starsagent-introspection-debugging
Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.
246.3K Starsnarrow-react-prop-types
narrow React component prop types to match live code paths
3.1K Starscode-review
Reviews a supplied code path or diff for correctness, security, maintainability, and style without executing or modifying it
639 StarsOwner published · Review required
Install targets
Codex install prompt
Install the "baoyu-cover-image" agent skill from https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-cover-image. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Generates article cover images with 5 dimensions (type, palette, rendering, text, mood) combining 11 color palettes and 7 rendering styles. Supports cinematic (2.35:1), widescreen (16:9), and square (1:1) aspects. Use when user asks to "generate cover image", "create article cover", or "make cover". After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"jimliu-baoyu-skills-baoyu-cover-image","task":"Install baoyu-cover-image","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.See what it makes
ImagesCreate a technology article cover with one forceful headline, geometric color bands and a quiet subtitle area.
ImagesCreate a sustainable-living article cover using flowing landscape contours, organic texture and readable typography.
Supply asset profile
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Scenario
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Agent fit
Claude Code + OpenAI Agents + Cursor
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-cover-image --skill "baoyu-cover-image"
Maintenance
active
2mo since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
26K
80/100 Quality · 82/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · Published by the site owner. Automated review approval and runtime verification are not implied.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Owner published · Review requiredPublished by the site owner. Automated review approval and runtime verification are not implied.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Review the pinned source before installing.
Stars
26K GitHub stars
Repo activity
26K stars, 2.9K forks
Maintenance
2mo since push
License
MIT
Install
npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-cover-image --skill "baoyu-cover-image"
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-cover-image --skill "baoyu-cover-image"Do not use when
Alternative
40.4K Stars
npx skills add PatrickJS/awesome-cursorrules
Alternative
246.3K Stars
npx skills add affaan-m/ECC --skill agent-introspection-debugging
Alternative
3.1K Stars
npx skills add humanlayer/skills --skill narrow-react-prop-types
Alternative
639 Stars
npx skills add sandbaseai/sandbase-harness --skill code-review
Agent safety v2
Published by the site owner. Automated review approval and runtime verification are not implied.
Inspect the pinned source and approve installation explicitly in an isolated workspace.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20baoyu-cover-image%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20baoyu-cover-image%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/jimliu-baoyu-skills-baoyu-cover-image/install
Agent should check
Copy prompt
Task: Use baoyu-cover-image in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20baoyu-cover-image%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/jimliu-baoyu-skills-baoyu-cover-image/install
Install command: npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-cover-image --skill "baoyu-cover-image"
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/jimliu-baoyu-skills-baoyu-cover-image/install
LLM text format
/api/skills/jimliu-baoyu-skills-baoyu-cover-image/install?format=text
Find alternatives
/api/skills/search?q=baoyu-cover-image&limit=3
Agent prompt
Use baoyu-cover-image for this task. Review https://www.openagentskill.com/api/skills/jimliu-baoyu-skills-baoyu-cover-image/install, then install with: npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-cover-image --skill "baoyu-cover-image"Registry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/jimliu-baoyu-skills-baoyu-cover-image
LLM text
/api/registry/manifest/jimliu-baoyu-skills-baoyu-cover-image?format=text
Install alias
/api/registry/install/jimliu-baoyu-skills-baoyu-cover-image
Recommend
/api/registry/recommend?task=Use%20baoyu-cover-image%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code, OpenAI Agents, Cursor
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Published by the site owner. Automated review approval and runtime verification are not implied.
Role in stack
Needs validation
Primary fit
Research agents
Trust label
Needs manual review
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Published by the site owner. Automated review approval and runtime verification are not implied.
GitHub adoption
PASS26K GitHub stars
Stars/forks activity
PASS26K stars, 2.9K forks; issue activity unavailable in current metadata
Recent maintenance
PASS2mo since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Review the pinned source before installing.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Parse messy files
I need my agent to read PDFs, extract tables, and turn documents into structured data.
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Workflow fit
Inspect, patch, and verify code
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Alternative shortlist
Similar skills that may fit this task.
A curated collection of cursor rules for various frameworks and technologies
Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.
narrow React component prop types to match live code paths
Reviews a supplied code path or diff for correctness, security, maintainability, and style without executing or modifying it
--- name: baoyu-cover-image description: Generates article cover images with 5 dimensions (type, palette, rendering, text, mood) combining 11 color palettes and 7 rendering styles. Supports cinematic (2.35:1), widescreen (16:9), and square (1:1) aspects. Use when user asks to "generate cover image", "create article cover", or "make cover". version: 1.117.5 metadata: openclaw: homepage: https://github.com/JimLiu/baoyu-skills#baoyu-cover-image ---
# Cover Image Generator
Generate elegant cover images for articles with 5-dimensional customization.
## User Input Tools
When this skill prompts the user, follow this tool-selection rule (priority order):
1. **Prefer built-in user-input tools** exposed by the current agent runtime — e.g., `AskUserQuestion`, `request_user_input`, `clarify`, `ask_user`, or any equivalent. 2. **Fallback**: if no such tool exists, emit a numbered plain-text message and ask the user to reply with the chosen number/answer for each question. 3. **Batching**: if the tool supports multiple questions per call, combine all applicable questions into a single call; if only single-question, ask them one at a time in priority order.
Concrete `AskUserQuestion` references below are examples — substitute the local equivalent in other runtimes.
## Image Generation Tools
When this skill needs to render an image, resolve the backend in this order:
1. **Current-request override** — if the user names a specific backend in the current message, use it. 2. **Saved preference** — if `EXTEND.md` sets `preferred_image_backend` to a backend available right now, use it. 3. **Auto-select** (when the preference is `auto`, unset, or the pinned backend isn't available): - **Codex (`imagegen`)** — first, inspect your available-skills / tool inventory. If a skill named `imagegen` is listed, you are running inside Codex and MUST use it: invoke via the `Skill` tool with `skill: "imagegen"`, passing the saved prompt file's content (plus output path and aspect ratio per Codex `imagegen`'s own args). Codex `imagegen` is the official raster backend in that runtime and outranks any non-native skill (e.g., `baoyu-image-gen`) unless the user has explicitly pinned a different `preferred_image_backend`. - **Codex via `codex exec` (`codex-imagegen`)** — if the current runtime exposes no native `imagegen` skill but the `codex` CLI is on `PATH` with an active `codex login`, route through `baoyu-image-gen --provider codex-cli` (preferred), or — if baoyu-image-gen is unavailable — invoke the bundled wrapper directly. Details, parameters, and the runtime-discovery procedure live in [references/codex-imagegen.md](references/codex-imagegen.md) — load that file only when this branch is selected. - **Cursor (`GenerateImage`)** — if the runtime exposes a native `GenerateImage` tool, you are running inside Cursor and it outranks any non-native skill the same way Codex `imagegen` does. Two hard caveats: (a) it has no aspect-ratio parameter — state the target aspect ratio / dimensions explicitly in the prompt text passed as `description`; (b) it does not accept an output directory — it saves to a tool-managed location, so after generation copy/move the file to the skill's expected output path (e.g., `outputs/.../NN-xxx.png`). Reference images go in `reference_image_paths`. - **Other runtime-native tools** — if the runtime exposes a different native image tool (e.g., Hermes `image_generate`), use it the same way. - Otherwise, if exactly one non-native backend is installed (e.g., `baoyu-image-gen`), use it. - Otherwise (multiple non-native backends with no runtime-native tool), ask the user once — batch with any other initial questions. 4. **If none are available**, tell the user and ask how to proceed.
**⛔ Never substitute SVG, HTML, canvas, or other code-based rendering for raster image generation.** Codex `imagegen`'s own description says it should be used "when the output should be a bitmap asset rather than repo-native code or vector." If you cannot resolve a raster backend via step 3, fall through to step 4 and ask the user — do **not** silently emit SVG, write inline `<svg>` markup, or produce HTML/CSS art as a substitute. This applies even if the article/section seems "diagram-like": the consumer skill calling this rule has already decided that a raster image is what it needs.
**⛔ Never repair rendered text by painting over a generated bitmap.** Do not use ImageMagick, Pillow, Canvas, SVG, HTML/CSS, OCR scripts, or any other programmatic overlay to cover, rewrite, erase, stroke, or replace title/subtitle text inside an already generated cover image. If text is wrong or unclear, regenerate from a corrected prompt, switch to a lower-text or no-title variant, or ask the user which imperfect candidate to keep.
Setting `preferred_image_backend: ask` forces the step-3 prompt every run regardless of available backends. Users change the pinned backend via the `## Changing Preferences` section below.
**Prompt file requirement (hard)**: write each image's full, final prompt to a standalone file under `prompts/` (naming: `NN-{type}-[slug].md`) BEFORE invoking any backend. The backend receives the prompt file (or its content); the file is the reproducibility record and lets you switch backends without regenerating prompts.
Concrete tool names (`imagegen`, `GenerateImage`, `image_generate`, `baoyu-image-gen`) above are examples — substitute the local equivalents under the same rule.
## Confirmation Policy
Default behavior: **confirm before generation**.
- Treat explicit skill invocation, a file path, matched keywords/presets, `EXTEND.md` defaults, and any documented auto-selection as **recommendation inputs only**. None of them authorizes skipping confirmation. - Do **not** start Step 3 or Step 4 until the user confirms the dimensions / aspect / language / backend choices. - Skip confirmation only when the current request explicitly says to do so, for example: `--quick`, "直接生成", "不用确认", "跳过确认", "按默认出图", or equivalent wording. `quick_mode: true` in `EXTEND.md` counts as a standing explicit opt-out — set it only when you want every run to skip Step 2. - If confirmation is skipped explicitly, state the assumed dimensions / aspect / language / backend in the next user-facing update before generating.
## Options
| Option | Description | |--------|-------------| | `--type <name>` | hero, conceptual, typography, metaphor, scene, minimal | | `--palette <name>` | warm, elegant, cool, dark, earth, vivid, pastel, mono, retro, duotone, macaron | | `--rendering <name>` | flat-vector, hand-drawn, painterly, digital, pixel, chalk, screen-print | | `--style <name>` | Preset shorthand (see [Style Presets](references/style-presets.md)) | | `--text <level>` | none, title-only, title-subtitle, text-rich | | `--mood <level>` | subtle, balanced, bold | | `--font <name>` | clean, handwritten, serif, display | | `--aspect <ratio>` | 16:9 (default), 2.35:1, 4:3, 3:2, 1:1, 3:4 | | `--lang <code>` | Title language (en, zh, ja, etc.) | | `--no-title` | Alias for `--text none` | | `--quick` | Skip confirmation, use auto-selection | | `--ref <files...>` | Reference images for style/composition guidance |
## Five Dimensions
| Dimension | Values | Default | |-----------|--------|---------| | **Type** | hero, conceptual, typography, metaphor, scene, minimal | auto | | **Palette** | warm, elegant, cool, dark, earth, vivid, pastel, mono, retro, duotone, macaron | auto | | **Rendering** | flat-vector, hand-drawn, painterly, digital, pixel, chalk, screen-print | auto | | **Text** | none, title-only, title-subtitle, text-rich | title-only | | **Mood** | subtle, balanced, bold | balanced | | **Font** | clean, handwritten, serif, display | clean |
Auto-selection rules: [references/auto-selection.md](references/auto-selection.md)
## Galleries
**Types**: hero, conceptual, typography, metaphor, scene, minimal → Details: [references/types.md](references/types.md)
**Palettes**: warm, elegant, cool, dark, earth, vivid, pastel, mono, retro, duotone, macaron → Details: [references/palettes/](references/palettes/)
**Renderings**: flat-vector, hand-drawn, painterly, digital, pixel, chalk, screen-print → Details: [references/renderings/](references/renderings/)
**Text Levels**: none (pure visual) | title-only (default) | title-subtitle | text-rich (with tags) → Details: [references/dimensions/text.md](references/dimensions/text.md)
**Mood Levels**: subtle (low contrast) | balanced (default) | bold (high contrast) → Details: [references/dimensions/mood.md](references/dimensions/mood.md)
**Fonts**: clean (sans-serif) | handwritten | serif | display (bold decorative) → Details: [references/dimensions/font.md](references/dimensions/font.md)
## File Structure
Output directory per `default_output_dir` preference: - `same-dir`: `{article-dir}/` - `imgs-subdir`: `{article-dir}/imgs/` - `independent` (default): `cover-image/{topic-slug}/`
``` <output-dir>/ ├── source-{slug}.{ext} # Source files ├── refs/ # Reference images (if provided) │ ├── ref-01-{slug}.{ext} │ └── ref-01-{slug}.md # Description file ├── prompts/cover.md # Generation prompt └── cover.png # Output image ```
**Slug**: 2-4 words, kebab-case. Conflict: append `-YYYYMMDD-HHMMSS`
## Workflow
### Progress Checklist
``` Cover Image Progress: - [ ] Step 0: Check preferences (EXTEND.md) ⛔ BLOCKING - [ ] Step 1: Analyze content + save refs + determine output dir - [ ] Step 2: Confirm options (6 dimensions) ⚠️ unless --quick - [ ] Step 3: Create prompt - [ ] Step 4: Generate image - [ ] Step 5: Completion report ```
### Flow
``` Input → [Step 0: Preferences] ─┬─ Found → Continue └─ Not found → First-Time Setup ⛔ BLOCKING → Save EXTEND.md → Continue ↓ Analyze + Save Refs → [Output Dir] → [Confirm: 6 Dimensions] → Prompt → Generate → Complete ↓ (skip if --quick or all specified) ```
### Step 0: Load Preferences ⛔ BLOCKING
Check EXTEND.md in priority order — the first one found wins:
| Priority | Path | Scope | |----------|------|-------| | 1 | `.baoyu-skills/baoyu-cover-image/EXTEND.md` | Project | | 2 | `${XDG_CONFIG_HOME:-$HOME/.config}/baoyu-skills/baoyu-cover-image/EXTEND.md` | XDG | | 3 | `$HOME/.baoyu-skills/baoyu-cover-image/EXTEND.md` | User home |
| Result | Action | |--------|--------| | Found | Load, display summary → Continue | | Not found | ⛔ Run first-time setup ([references/config/first-time-setup.md](references/config/first-time-setup.md)) → Save → Continue |
**CRITICAL**: If not found, complete setup BEFORE any other steps or questions.
### Step 1: Analyze Content
1. **Save reference images** (if provided) → [references/workflow/reference-images.md](references/workflow/reference-images.md) 2. **Save source content** (if pasted, save to `source.md`) 3. **Analyze content**: topic, tone, keywords, visual metaphors 4. **Deep analyze references** ⚠️: Extract specific, concrete elements (see reference-images.md) 5. **Detect language**: Compare source, user input, EXTEND.md preference 6. **Determine output directory**: Per File Structure rules
**⚠️ People in Reference Images:**
If reference images contain **people** who should appear in the cover:
- **Model supports `--ref`** (default): Copy image to `refs/`, pass via `--ref` at generation. No description file needed — the model sees the face directly. - **Model does NOT support `--ref`** (Jimeng, Seedream 3.0): Create `refs/ref-NN-{slug}.md` with per-character description (hair, glasses, skin tone, clothing). Embed as MUST/REQUIRED instructions in prompt text.
See [reference-images.md](references/workflow/reference-images.md) for full decision table.
### Step 2: Confirm Options ⚠️
**Hard gate**: this step is mandatory per the [Confirmation Policy](#confirmation-policy) — Steps 3–4 cannot start until the user confirms
Source provenance
Decision snapshot
25,722 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for baoyu-cover-image, ready for a manual X post.
baoyu-cover-image: Generates article cover images with 5 dimensions (type, palette, rendering, text, mood) combi... 25.7K stars https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-cover-image?ref=x
Listing + install path for baoyu-cover-image: https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-cover-image?ref=x Install: npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0...
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
This Registry indexed listing is attributed to JimLiu but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-cover-image?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-cover-image?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-cover-image/audit)
[](https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-cover-image?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)JimLiu
@jimliu
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Owner published · Review required
Cursor Rules
A curated collection of cursor rules for various frameworks and technologies
40.4K Starsagent-introspection-debugging
Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.
246.3K Starsnarrow-react-prop-types
narrow React component prop types to match live code paths
3.1K Starscode-review
Reviews a supplied code path or diff for correctness, security, maintainability, and style without executing or modifying it
639 StarsOwner published · Review required
Install targets
Codex install prompt
Install the "baoyu-cover-image" agent skill from https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-cover-image. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Generates article cover images with 5 dimensions (type, palette, rendering, text, mood) combining 11 color palettes and 7 rendering styles. Supports cinematic (2.35:1), widescreen (16:9), and square (1:1) aspects. Use when user asks to "generate cover image", "create article cover", or "make cover". After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"jimliu-baoyu-skills-baoyu-cover-image","task":"Install baoyu-cover-image","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.See what it makes
ImagesCreate a technology article cover with one forceful headline, geometric color bands and a quiet subtitle area.
ImagesCreate a sustainable-living article cover using flowing landscape contours, organic texture and readable typography.
Supply asset profile
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Scenario
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Agent fit
Claude Code + OpenAI Agents + Cursor
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-cover-image --skill "baoyu-cover-image"
Maintenance
active
2mo since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
26K
80/100 Quality · 82/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · Published by the site owner. Automated review approval and runtime verification are not implied.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Owner published · Review requiredPublished by the site owner. Automated review approval and runtime verification are not implied.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Review the pinned source before installing.
Stars
26K GitHub stars
Repo activity
26K stars, 2.9K forks
Maintenance
2mo since push
License
MIT
Install
npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-cover-image --skill "baoyu-cover-image"
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-cover-image --skill "baoyu-cover-image"Do not use when
Alternative
40.4K Stars
npx skills add PatrickJS/awesome-cursorrules
Alternative
246.3K Stars
npx skills add affaan-m/ECC --skill agent-introspection-debugging
Alternative
3.1K Stars
npx skills add humanlayer/skills --skill narrow-react-prop-types
Alternative
639 Stars
npx skills add sandbaseai/sandbase-harness --skill code-review
Agent safety v2
Published by the site owner. Automated review approval and runtime verification are not implied.
Inspect the pinned source and approve installation explicitly in an isolated workspace.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20baoyu-cover-image%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20baoyu-cover-image%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/jimliu-baoyu-skills-baoyu-cover-image/install
Agent should check
Copy prompt
Task: Use baoyu-cover-image in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20baoyu-cover-image%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/jimliu-baoyu-skills-baoyu-cover-image/install
Install command: npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-cover-image --skill "baoyu-cover-image"
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/jimliu-baoyu-skills-baoyu-cover-image/install
LLM text format
/api/skills/jimliu-baoyu-skills-baoyu-cover-image/install?format=text
Find alternatives
/api/skills/search?q=baoyu-cover-image&limit=3
Agent prompt
Use baoyu-cover-image for this task. Review https://www.openagentskill.com/api/skills/jimliu-baoyu-skills-baoyu-cover-image/install, then install with: npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0b168332f4142584617/skills/baoyu-cover-image --skill "baoyu-cover-image"Registry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/jimliu-baoyu-skills-baoyu-cover-image
LLM text
/api/registry/manifest/jimliu-baoyu-skills-baoyu-cover-image?format=text
Install alias
/api/registry/install/jimliu-baoyu-skills-baoyu-cover-image
Recommend
/api/registry/recommend?task=Use%20baoyu-cover-image%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code, OpenAI Agents, Cursor
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Published by the site owner. Automated review approval and runtime verification are not implied.
Role in stack
Needs validation
Primary fit
Research agents
Trust label
Needs manual review
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Published by the site owner. Automated review approval and runtime verification are not implied.
GitHub adoption
PASS26K GitHub stars
Stars/forks activity
PASS26K stars, 2.9K forks; issue activity unavailable in current metadata
Recent maintenance
PASS2mo since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Review the pinned source before installing.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Parse messy files
I need my agent to read PDFs, extract tables, and turn documents into structured data.
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Workflow fit
Inspect, patch, and verify code
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Alternative shortlist
Similar skills that may fit this task.
A curated collection of cursor rules for various frameworks and technologies
Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.
narrow React component prop types to match live code paths
Reviews a supplied code path or diff for correctness, security, maintainability, and style without executing or modifying it
--- name: baoyu-cover-image description: Generates article cover images with 5 dimensions (type, palette, rendering, text, mood) combining 11 color palettes and 7 rendering styles. Supports cinematic (2.35:1), widescreen (16:9), and square (1:1) aspects. Use when user asks to "generate cover image", "create article cover", or "make cover". version: 1.117.5 metadata: openclaw: homepage: https://github.com/JimLiu/baoyu-skills#baoyu-cover-image ---
# Cover Image Generator
Generate elegant cover images for articles with 5-dimensional customization.
## User Input Tools
When this skill prompts the user, follow this tool-selection rule (priority order):
1. **Prefer built-in user-input tools** exposed by the current agent runtime — e.g., `AskUserQuestion`, `request_user_input`, `clarify`, `ask_user`, or any equivalent. 2. **Fallback**: if no such tool exists, emit a numbered plain-text message and ask the user to reply with the chosen number/answer for each question. 3. **Batching**: if the tool supports multiple questions per call, combine all applicable questions into a single call; if only single-question, ask them one at a time in priority order.
Concrete `AskUserQuestion` references below are examples — substitute the local equivalent in other runtimes.
## Image Generation Tools
When this skill needs to render an image, resolve the backend in this order:
1. **Current-request override** — if the user names a specific backend in the current message, use it. 2. **Saved preference** — if `EXTEND.md` sets `preferred_image_backend` to a backend available right now, use it. 3. **Auto-select** (when the preference is `auto`, unset, or the pinned backend isn't available): - **Codex (`imagegen`)** — first, inspect your available-skills / tool inventory. If a skill named `imagegen` is listed, you are running inside Codex and MUST use it: invoke via the `Skill` tool with `skill: "imagegen"`, passing the saved prompt file's content (plus output path and aspect ratio per Codex `imagegen`'s own args). Codex `imagegen` is the official raster backend in that runtime and outranks any non-native skill (e.g., `baoyu-image-gen`) unless the user has explicitly pinned a different `preferred_image_backend`. - **Codex via `codex exec` (`codex-imagegen`)** — if the current runtime exposes no native `imagegen` skill but the `codex` CLI is on `PATH` with an active `codex login`, route through `baoyu-image-gen --provider codex-cli` (preferred), or — if baoyu-image-gen is unavailable — invoke the bundled wrapper directly. Details, parameters, and the runtime-discovery procedure live in [references/codex-imagegen.md](references/codex-imagegen.md) — load that file only when this branch is selected. - **Cursor (`GenerateImage`)** — if the runtime exposes a native `GenerateImage` tool, you are running inside Cursor and it outranks any non-native skill the same way Codex `imagegen` does. Two hard caveats: (a) it has no aspect-ratio parameter — state the target aspect ratio / dimensions explicitly in the prompt text passed as `description`; (b) it does not accept an output directory — it saves to a tool-managed location, so after generation copy/move the file to the skill's expected output path (e.g., `outputs/.../NN-xxx.png`). Reference images go in `reference_image_paths`. - **Other runtime-native tools** — if the runtime exposes a different native image tool (e.g., Hermes `image_generate`), use it the same way. - Otherwise, if exactly one non-native backend is installed (e.g., `baoyu-image-gen`), use it. - Otherwise (multiple non-native backends with no runtime-native tool), ask the user once — batch with any other initial questions. 4. **If none are available**, tell the user and ask how to proceed.
**⛔ Never substitute SVG, HTML, canvas, or other code-based rendering for raster image generation.** Codex `imagegen`'s own description says it should be used "when the output should be a bitmap asset rather than repo-native code or vector." If you cannot resolve a raster backend via step 3, fall through to step 4 and ask the user — do **not** silently emit SVG, write inline `<svg>` markup, or produce HTML/CSS art as a substitute. This applies even if the article/section seems "diagram-like": the consumer skill calling this rule has already decided that a raster image is what it needs.
**⛔ Never repair rendered text by painting over a generated bitmap.** Do not use ImageMagick, Pillow, Canvas, SVG, HTML/CSS, OCR scripts, or any other programmatic overlay to cover, rewrite, erase, stroke, or replace title/subtitle text inside an already generated cover image. If text is wrong or unclear, regenerate from a corrected prompt, switch to a lower-text or no-title variant, or ask the user which imperfect candidate to keep.
Setting `preferred_image_backend: ask` forces the step-3 prompt every run regardless of available backends. Users change the pinned backend via the `## Changing Preferences` section below.
**Prompt file requirement (hard)**: write each image's full, final prompt to a standalone file under `prompts/` (naming: `NN-{type}-[slug].md`) BEFORE invoking any backend. The backend receives the prompt file (or its content); the file is the reproducibility record and lets you switch backends without regenerating prompts.
Concrete tool names (`imagegen`, `GenerateImage`, `image_generate`, `baoyu-image-gen`) above are examples — substitute the local equivalents under the same rule.
## Confirmation Policy
Default behavior: **confirm before generation**.
- Treat explicit skill invocation, a file path, matched keywords/presets, `EXTEND.md` defaults, and any documented auto-selection as **recommendation inputs only**. None of them authorizes skipping confirmation. - Do **not** start Step 3 or Step 4 until the user confirms the dimensions / aspect / language / backend choices. - Skip confirmation only when the current request explicitly says to do so, for example: `--quick`, "直接生成", "不用确认", "跳过确认", "按默认出图", or equivalent wording. `quick_mode: true` in `EXTEND.md` counts as a standing explicit opt-out — set it only when you want every run to skip Step 2. - If confirmation is skipped explicitly, state the assumed dimensions / aspect / language / backend in the next user-facing update before generating.
## Options
| Option | Description | |--------|-------------| | `--type <name>` | hero, conceptual, typography, metaphor, scene, minimal | | `--palette <name>` | warm, elegant, cool, dark, earth, vivid, pastel, mono, retro, duotone, macaron | | `--rendering <name>` | flat-vector, hand-drawn, painterly, digital, pixel, chalk, screen-print | | `--style <name>` | Preset shorthand (see [Style Presets](references/style-presets.md)) | | `--text <level>` | none, title-only, title-subtitle, text-rich | | `--mood <level>` | subtle, balanced, bold | | `--font <name>` | clean, handwritten, serif, display | | `--aspect <ratio>` | 16:9 (default), 2.35:1, 4:3, 3:2, 1:1, 3:4 | | `--lang <code>` | Title language (en, zh, ja, etc.) | | `--no-title` | Alias for `--text none` | | `--quick` | Skip confirmation, use auto-selection | | `--ref <files...>` | Reference images for style/composition guidance |
## Five Dimensions
| Dimension | Values | Default | |-----------|--------|---------| | **Type** | hero, conceptual, typography, metaphor, scene, minimal | auto | | **Palette** | warm, elegant, cool, dark, earth, vivid, pastel, mono, retro, duotone, macaron | auto | | **Rendering** | flat-vector, hand-drawn, painterly, digital, pixel, chalk, screen-print | auto | | **Text** | none, title-only, title-subtitle, text-rich | title-only | | **Mood** | subtle, balanced, bold | balanced | | **Font** | clean, handwritten, serif, display | clean |
Auto-selection rules: [references/auto-selection.md](references/auto-selection.md)
## Galleries
**Types**: hero, conceptual, typography, metaphor, scene, minimal → Details: [references/types.md](references/types.md)
**Palettes**: warm, elegant, cool, dark, earth, vivid, pastel, mono, retro, duotone, macaron → Details: [references/palettes/](references/palettes/)
**Renderings**: flat-vector, hand-drawn, painterly, digital, pixel, chalk, screen-print → Details: [references/renderings/](references/renderings/)
**Text Levels**: none (pure visual) | title-only (default) | title-subtitle | text-rich (with tags) → Details: [references/dimensions/text.md](references/dimensions/text.md)
**Mood Levels**: subtle (low contrast) | balanced (default) | bold (high contrast) → Details: [references/dimensions/mood.md](references/dimensions/mood.md)
**Fonts**: clean (sans-serif) | handwritten | serif | display (bold decorative) → Details: [references/dimensions/font.md](references/dimensions/font.md)
## File Structure
Output directory per `default_output_dir` preference: - `same-dir`: `{article-dir}/` - `imgs-subdir`: `{article-dir}/imgs/` - `independent` (default): `cover-image/{topic-slug}/`
``` <output-dir>/ ├── source-{slug}.{ext} # Source files ├── refs/ # Reference images (if provided) │ ├── ref-01-{slug}.{ext} │ └── ref-01-{slug}.md # Description file ├── prompts/cover.md # Generation prompt └── cover.png # Output image ```
**Slug**: 2-4 words, kebab-case. Conflict: append `-YYYYMMDD-HHMMSS`
## Workflow
### Progress Checklist
``` Cover Image Progress: - [ ] Step 0: Check preferences (EXTEND.md) ⛔ BLOCKING - [ ] Step 1: Analyze content + save refs + determine output dir - [ ] Step 2: Confirm options (6 dimensions) ⚠️ unless --quick - [ ] Step 3: Create prompt - [ ] Step 4: Generate image - [ ] Step 5: Completion report ```
### Flow
``` Input → [Step 0: Preferences] ─┬─ Found → Continue └─ Not found → First-Time Setup ⛔ BLOCKING → Save EXTEND.md → Continue ↓ Analyze + Save Refs → [Output Dir] → [Confirm: 6 Dimensions] → Prompt → Generate → Complete ↓ (skip if --quick or all specified) ```
### Step 0: Load Preferences ⛔ BLOCKING
Check EXTEND.md in priority order — the first one found wins:
| Priority | Path | Scope | |----------|------|-------| | 1 | `.baoyu-skills/baoyu-cover-image/EXTEND.md` | Project | | 2 | `${XDG_CONFIG_HOME:-$HOME/.config}/baoyu-skills/baoyu-cover-image/EXTEND.md` | XDG | | 3 | `$HOME/.baoyu-skills/baoyu-cover-image/EXTEND.md` | User home |
| Result | Action | |--------|--------| | Found | Load, display summary → Continue | | Not found | ⛔ Run first-time setup ([references/config/first-time-setup.md](references/config/first-time-setup.md)) → Save → Continue |
**CRITICAL**: If not found, complete setup BEFORE any other steps or questions.
### Step 1: Analyze Content
1. **Save reference images** (if provided) → [references/workflow/reference-images.md](references/workflow/reference-images.md) 2. **Save source content** (if pasted, save to `source.md`) 3. **Analyze content**: topic, tone, keywords, visual metaphors 4. **Deep analyze references** ⚠️: Extract specific, concrete elements (see reference-images.md) 5. **Detect language**: Compare source, user input, EXTEND.md preference 6. **Determine output directory**: Per File Structure rules
**⚠️ People in Reference Images:**
If reference images contain **people** who should appear in the cover:
- **Model supports `--ref`** (default): Copy image to `refs/`, pass via `--ref` at generation. No description file needed — the model sees the face directly. - **Model does NOT support `--ref`** (Jimeng, Seedream 3.0): Create `refs/ref-NN-{slug}.md` with per-character description (hair, glasses, skin tone, clothing). Embed as MUST/REQUIRED instructions in prompt text.
See [reference-images.md](references/workflow/reference-images.md) for full decision table.
### Step 2: Confirm Options ⚠️
**Hard gate**: this step is mandatory per the [Confirmation Policy](#confirmation-policy) — Steps 3–4 cannot start until the user confirms
Source provenance
Decision snapshot
25,722 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for baoyu-cover-image, ready for a manual X post.
baoyu-cover-image: Generates article cover images with 5 dimensions (type, palette, rendering, text, mood) combi... 25.7K stars https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-cover-image?ref=x
Listing + install path for baoyu-cover-image: https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-cover-image?ref=x Install: npx skills add https://github.com/JimLiu/baoyu-skills/tree/6b7a2e417500561a5ecdd0...
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
This Registry indexed listing is attributed to JimLiu but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-cover-image?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-cover-image?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-cover-image/audit)
[](https://www.openagentskill.com/skills/jimliu-baoyu-skills-baoyu-cover-image?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)JimLiu
@jimliu
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Owner published · Review required
Cursor Rules
A curated collection of cursor rules for various frameworks and technologies
40.4K Starsagent-introspection-debugging
Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.
246.3K Starsnarrow-react-prop-types
narrow React component prop types to match live code paths
3.1K Starscode-review
Reviews a supplied code path or diff for correctness, security, maintainability, and style without executing or modifying it
639 Starsstandard package or runtime install path
Permission surface
shell or command execution, filesystem or document access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness
standard package or runtime install path
Permission surface
shell or command execution, filesystem or document access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness
standard package or runtime install path
Permission surface
shell or command execution, filesystem or document access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness
standard package or runtime install path
Permission surface
shell or command execution, filesystem or document access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness