Creator · zhnnky329
Last updated · Sep 5, 2026
Generate and render-verify publication-quality mathematical-modeling figures from saved evidence, using the approved figure plan, source data, claim, type, and consistent visual system.
Creator · zhnnky329
Last updated · Sep 5, 2026
Generate and render-verify publication-quality mathematical-modeling figures from saved evidence, using the approved figure plan, source data, claim, type, and consistent visual system.
Creator · zhnnky329
Last updated · Sep 5, 2026
Generate and render-verify publication-quality mathematical-modeling figures from saved evidence, using the approved figure plan, source data, claim, type, and consistent visual system.
Creator · zhnnky329
Last updated · Sep 5, 2026
Generate and render-verify publication-quality mathematical-modeling figures from saved evidence, using the approved figure plan, source data, claim, type, and consistent visual system.
Sandbox only
Install targets
Codex install prompt
Install the "math-figure-generator" agent skill from https://github.com/zhnnky329/MathModeling-skills/tree/main/.claude/skills/math-figure-generator. 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: Generate and render-verify publication-quality mathematical-modeling figures from saved evidence, using the approved figure plan, source data, claim, type, and consistent visual system. 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":"zhnnky329-math-figure-generator","task":"Install math-figure-generator","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.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add zhnnky329/MathModeling-skills --skill math-figure-generator
Maintenance
fresh
12d since push
Risk
Needs review
SKILL.md does not define the meaning of 'Type 3' and 'Type 1/2/4' claims, which may be unclear to users outside the original project context.
GitHub quality
723
75/100 Quality · 74/100 Trust
Coverage tags
Review notes
SKILL.md does not define the meaning of 'Type 3' and 'Type 1/2/4' claims, which may be unclear to users outside the original project context. · No explicit limitations or safe operating boundaries are described in SKILL.md, such as acceptable input formats or behavior when source data is missing or invalid.
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
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
723 GitHub stars
Repo activity
723 stars, 32 forks
Maintenance
12d since push
License
MIT
Install
npx skills add zhnnky329/MathModeling-skills --skill math-figure-generator
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 zhnnky329/MathModeling-skills --skill math-figure-generatorDo not use when
Alternative
1.9K Stars
npx skills add yanliudesign/mono-color-skill --skill mono-color
Alternative
61.0K Stars
npx skills add mvanhorn/last30days-skill -g
Alternative
38.4K Stars
npx skills add Imbad0202/academic-research-skills
Alternative
28.0K Stars
npx skills add assafelovic/gpt-researcher
Agent safety v2
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
medium
Skill may drive a browser or interact with web pages.
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%20math-figure-generator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20math-figure-generator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/zhnnky329-math-figure-generator/install
Agent should check
Copy prompt
Task: Use math-figure-generator in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20math-figure-generator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/zhnnky329-math-figure-generator/install
Install command: npx skills add zhnnky329/MathModeling-skills --skill math-figure-generator
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/zhnnky329-math-figure-generator/install
LLM text format
/api/skills/zhnnky329-math-figure-generator/install?format=text
Find alternatives
/api/skills/search?q=math-figure-generator&limit=3
Agent prompt
Use math-figure-generator for this task. Review https://www.openagentskill.com/api/skills/zhnnky329-math-figure-generator/install, then install with: npx skills add zhnnky329/MathModeling-skills --skill math-figure-generatorRegistry 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/zhnnky329-math-figure-generator
LLM text
/api/registry/manifest/zhnnky329-math-figure-generator?format=text
Install alias
/api/registry/install/zhnnky329-math-figure-generator
Recommend
/api/registry/recommend?task=Use%20math-figure-generator%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Research agents
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO723 GitHub stars
Stars/forks activity
INFO723 stars, 32 forks; issue activity unavailable in current metadata
Recent maintenance
PASS12d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
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.
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Workflow fit
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Alternative shortlist
Similar skills that may fit this task.
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills for Claude Code: research → write → review → revise → finalize
Run autonomous deep research over web and local sources
--- name: math-figure-generator description: Generate and render-verify publication-quality mathematical-modeling figures from saved evidence, using the approved figure plan, source data, claim, type, and consistent visual system. ---
# Preconditions
- Figure type, source artifacts, and target claim are known. - Type 3 claim is human-confirmed. - Submission figures use final/frozen evidence.
# References
Load only what the requested chart needs:
- `references/chart-patterns.md` - `references/color-systems.md` - `references/layout-guide.md` - `references/render-check.md`
# Workflow
1. Verify source files and the exact variables/units to plot. 2. Choose the smallest chart form that communicates the claim. 3. Generate with deterministic code, preferably matplotlib. 4. Save editable source code and the requested output format. 5. Apply the shared color, typography, sizing, and labeling conventions. 6. Render the final output and inspect it visually. 7. Check clipping, overlap, illegible text, misleading axes, legends, empty panels, and source/claim mismatch. 8. Iterate until render checks pass.
# Output Locations
- Type 1/2 exploration: `results/Qx/experiments/roundN/figures/` - Type 3/4 submission: `paper/figures/`
Use stable descriptive filenames. Do not copy Type 1 diagnostics into the paper directory.
# Figure Requirements
- Labels include units where applicable. - Captions state what is shown and the evidence-backed takeaway without overstating causality. - Baseline is visually distinct but not exaggerated. - Uncertainty is shown when it is part of the claim. - Type 3 raster output is at least 300 dpi; vector output is preferred when compatible. - Accessibility and grayscale differentiation are considered.
# Rules
- Do not fabricate or manually alter plotted values. - Do not use a chart type that hides concentration, uncertainty, or negative results. - Do not truncate axes misleadingly. - Do not create decorative 3D effects. - Do not treat code execution as render verification. - Keep diagnostic and paper roles separate.
# Verification
- Source, claim, type, and target section agree. - Render inspection passed. - Text is readable at final paper size. - Legends, colors, markers, axes, units, and captions are consistent. - Final output path exists and is recorded in the figure plan.
Source provenance
Decision snapshot
723 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 math-figure-generator, ready for a manual X post.
math-figure-generator: Generate and render-verify publication-quality mathematical-modeling figures from saved evide... 723 stars https://www.openagentskill.com/skills/zhnnky329-math-figure-generator?ref=x
Listing + install path for math-figure-generator: https://www.openagentskill.com/skills/zhnnky329-math-figure-generator?ref=x Install: npx skills add zhnnky329/MathModeling-skills --skill math-figure-generator
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 zhnnky329 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/zhnnky329-math-figure-generator?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/zhnnky329-math-figure-generator?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/zhnnky329-math-figure-generator/audit)
[](https://www.openagentskill.com/skills/zhnnky329-math-figure-generator?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)zhnnky329
@zhnnky329
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Sandbox only
mono-color
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1.9K StarsLast30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
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Academic Research Skills for Claude Code: research → write → review → revise → finalize
38.4K StarsGPT Researcher
Run autonomous deep research over web and local sources
28.0K StarsSandbox only
Install targets
Codex install prompt
Install the "math-figure-generator" agent skill from https://github.com/zhnnky329/MathModeling-skills/tree/main/.claude/skills/math-figure-generator. 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: Generate and render-verify publication-quality mathematical-modeling figures from saved evidence, using the approved figure plan, source data, claim, type, and consistent visual system. 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":"zhnnky329-math-figure-generator","task":"Install math-figure-generator","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.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add zhnnky329/MathModeling-skills --skill math-figure-generator
Maintenance
fresh
12d since push
Risk
Needs review
SKILL.md does not define the meaning of 'Type 3' and 'Type 1/2/4' claims, which may be unclear to users outside the original project context.
GitHub quality
723
75/100 Quality · 74/100 Trust
Coverage tags
Review notes
SKILL.md does not define the meaning of 'Type 3' and 'Type 1/2/4' claims, which may be unclear to users outside the original project context. · No explicit limitations or safe operating boundaries are described in SKILL.md, such as acceptable input formats or behavior when source data is missing or invalid.
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
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
723 GitHub stars
Repo activity
723 stars, 32 forks
Maintenance
12d since push
License
MIT
Install
npx skills add zhnnky329/MathModeling-skills --skill math-figure-generator
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 zhnnky329/MathModeling-skills --skill math-figure-generatorDo not use when
Alternative
1.9K Stars
npx skills add yanliudesign/mono-color-skill --skill mono-color
Alternative
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npx skills add mvanhorn/last30days-skill -g
Alternative
38.4K Stars
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Alternative
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npx skills add assafelovic/gpt-researcher
Agent safety v2
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
medium
Skill may drive a browser or interact with web pages.
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%20math-figure-generator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20math-figure-generator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/zhnnky329-math-figure-generator/install
Agent should check
Copy prompt
Task: Use math-figure-generator in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20math-figure-generator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/zhnnky329-math-figure-generator/install
Install command: npx skills add zhnnky329/MathModeling-skills --skill math-figure-generator
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/zhnnky329-math-figure-generator/install
LLM text format
/api/skills/zhnnky329-math-figure-generator/install?format=text
Find alternatives
/api/skills/search?q=math-figure-generator&limit=3
Agent prompt
Use math-figure-generator for this task. Review https://www.openagentskill.com/api/skills/zhnnky329-math-figure-generator/install, then install with: npx skills add zhnnky329/MathModeling-skills --skill math-figure-generatorRegistry 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/zhnnky329-math-figure-generator
LLM text
/api/registry/manifest/zhnnky329-math-figure-generator?format=text
Install alias
/api/registry/install/zhnnky329-math-figure-generator
Recommend
/api/registry/recommend?task=Use%20math-figure-generator%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Research agents
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO723 GitHub stars
Stars/forks activity
INFO723 stars, 32 forks; issue activity unavailable in current metadata
Recent maintenance
PASS12d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
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.
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Workflow fit
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Alternative shortlist
Similar skills that may fit this task.
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills for Claude Code: research → write → review → revise → finalize
Run autonomous deep research over web and local sources
--- name: math-figure-generator description: Generate and render-verify publication-quality mathematical-modeling figures from saved evidence, using the approved figure plan, source data, claim, type, and consistent visual system. ---
# Preconditions
- Figure type, source artifacts, and target claim are known. - Type 3 claim is human-confirmed. - Submission figures use final/frozen evidence.
# References
Load only what the requested chart needs:
- `references/chart-patterns.md` - `references/color-systems.md` - `references/layout-guide.md` - `references/render-check.md`
# Workflow
1. Verify source files and the exact variables/units to plot. 2. Choose the smallest chart form that communicates the claim. 3. Generate with deterministic code, preferably matplotlib. 4. Save editable source code and the requested output format. 5. Apply the shared color, typography, sizing, and labeling conventions. 6. Render the final output and inspect it visually. 7. Check clipping, overlap, illegible text, misleading axes, legends, empty panels, and source/claim mismatch. 8. Iterate until render checks pass.
# Output Locations
- Type 1/2 exploration: `results/Qx/experiments/roundN/figures/` - Type 3/4 submission: `paper/figures/`
Use stable descriptive filenames. Do not copy Type 1 diagnostics into the paper directory.
# Figure Requirements
- Labels include units where applicable. - Captions state what is shown and the evidence-backed takeaway without overstating causality. - Baseline is visually distinct but not exaggerated. - Uncertainty is shown when it is part of the claim. - Type 3 raster output is at least 300 dpi; vector output is preferred when compatible. - Accessibility and grayscale differentiation are considered.
# Rules
- Do not fabricate or manually alter plotted values. - Do not use a chart type that hides concentration, uncertainty, or negative results. - Do not truncate axes misleadingly. - Do not create decorative 3D effects. - Do not treat code execution as render verification. - Keep diagnostic and paper roles separate.
# Verification
- Source, claim, type, and target section agree. - Render inspection passed. - Text is readable at final paper size. - Legends, colors, markers, axes, units, and captions are consistent. - Final output path exists and is recorded in the figure plan.
Source provenance
Decision snapshot
723 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 math-figure-generator, ready for a manual X post.
math-figure-generator: Generate and render-verify publication-quality mathematical-modeling figures from saved evide... 723 stars https://www.openagentskill.com/skills/zhnnky329-math-figure-generator?ref=x
Listing + install path for math-figure-generator: https://www.openagentskill.com/skills/zhnnky329-math-figure-generator?ref=x Install: npx skills add zhnnky329/MathModeling-skills --skill math-figure-generator
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 zhnnky329 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/zhnnky329-math-figure-generator?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/zhnnky329-math-figure-generator?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/zhnnky329-math-figure-generator/audit)
[](https://www.openagentskill.com/skills/zhnnky329-math-figure-generator?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)zhnnky329
@zhnnky329
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Sandbox only
mono-color
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
1.9K StarsLast30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
61.0K StarsAcademic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
38.4K StarsGPT Researcher
Run autonomous deep research over web and local sources
28.0K StarsSandbox only
Install targets
Codex install prompt
Install the "math-figure-generator" agent skill from https://github.com/zhnnky329/MathModeling-skills/tree/main/.claude/skills/math-figure-generator. 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: Generate and render-verify publication-quality mathematical-modeling figures from saved evidence, using the approved figure plan, source data, claim, type, and consistent visual system. 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":"zhnnky329-math-figure-generator","task":"Install math-figure-generator","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.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add zhnnky329/MathModeling-skills --skill math-figure-generator
Maintenance
fresh
12d since push
Risk
Needs review
SKILL.md does not define the meaning of 'Type 3' and 'Type 1/2/4' claims, which may be unclear to users outside the original project context.
GitHub quality
723
75/100 Quality · 74/100 Trust
Coverage tags
Review notes
SKILL.md does not define the meaning of 'Type 3' and 'Type 1/2/4' claims, which may be unclear to users outside the original project context. · No explicit limitations or safe operating boundaries are described in SKILL.md, such as acceptable input formats or behavior when source data is missing or invalid.
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
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
723 GitHub stars
Repo activity
723 stars, 32 forks
Maintenance
12d since push
License
MIT
Install
npx skills add zhnnky329/MathModeling-skills --skill math-figure-generator
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 zhnnky329/MathModeling-skills --skill math-figure-generatorDo not use when
Alternative
1.9K Stars
npx skills add yanliudesign/mono-color-skill --skill mono-color
Alternative
61.0K Stars
npx skills add mvanhorn/last30days-skill -g
Alternative
38.4K Stars
npx skills add Imbad0202/academic-research-skills
Alternative
28.0K Stars
npx skills add assafelovic/gpt-researcher
Agent safety v2
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
medium
Skill may drive a browser or interact with web pages.
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%20math-figure-generator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20math-figure-generator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/zhnnky329-math-figure-generator/install
Agent should check
Copy prompt
Task: Use math-figure-generator in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20math-figure-generator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/zhnnky329-math-figure-generator/install
Install command: npx skills add zhnnky329/MathModeling-skills --skill math-figure-generator
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/zhnnky329-math-figure-generator/install
LLM text format
/api/skills/zhnnky329-math-figure-generator/install?format=text
Find alternatives
/api/skills/search?q=math-figure-generator&limit=3
Agent prompt
Use math-figure-generator for this task. Review https://www.openagentskill.com/api/skills/zhnnky329-math-figure-generator/install, then install with: npx skills add zhnnky329/MathModeling-skills --skill math-figure-generatorRegistry 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/zhnnky329-math-figure-generator
LLM text
/api/registry/manifest/zhnnky329-math-figure-generator?format=text
Install alias
/api/registry/install/zhnnky329-math-figure-generator
Recommend
/api/registry/recommend?task=Use%20math-figure-generator%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Research agents
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO723 GitHub stars
Stars/forks activity
INFO723 stars, 32 forks; issue activity unavailable in current metadata
Recent maintenance
PASS12d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
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.
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Workflow fit
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Alternative shortlist
Similar skills that may fit this task.
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills for Claude Code: research → write → review → revise → finalize
Run autonomous deep research over web and local sources
--- name: math-figure-generator description: Generate and render-verify publication-quality mathematical-modeling figures from saved evidence, using the approved figure plan, source data, claim, type, and consistent visual system. ---
# Preconditions
- Figure type, source artifacts, and target claim are known. - Type 3 claim is human-confirmed. - Submission figures use final/frozen evidence.
# References
Load only what the requested chart needs:
- `references/chart-patterns.md` - `references/color-systems.md` - `references/layout-guide.md` - `references/render-check.md`
# Workflow
1. Verify source files and the exact variables/units to plot. 2. Choose the smallest chart form that communicates the claim. 3. Generate with deterministic code, preferably matplotlib. 4. Save editable source code and the requested output format. 5. Apply the shared color, typography, sizing, and labeling conventions. 6. Render the final output and inspect it visually. 7. Check clipping, overlap, illegible text, misleading axes, legends, empty panels, and source/claim mismatch. 8. Iterate until render checks pass.
# Output Locations
- Type 1/2 exploration: `results/Qx/experiments/roundN/figures/` - Type 3/4 submission: `paper/figures/`
Use stable descriptive filenames. Do not copy Type 1 diagnostics into the paper directory.
# Figure Requirements
- Labels include units where applicable. - Captions state what is shown and the evidence-backed takeaway without overstating causality. - Baseline is visually distinct but not exaggerated. - Uncertainty is shown when it is part of the claim. - Type 3 raster output is at least 300 dpi; vector output is preferred when compatible. - Accessibility and grayscale differentiation are considered.
# Rules
- Do not fabricate or manually alter plotted values. - Do not use a chart type that hides concentration, uncertainty, or negative results. - Do not truncate axes misleadingly. - Do not create decorative 3D effects. - Do not treat code execution as render verification. - Keep diagnostic and paper roles separate.
# Verification
- Source, claim, type, and target section agree. - Render inspection passed. - Text is readable at final paper size. - Legends, colors, markers, axes, units, and captions are consistent. - Final output path exists and is recorded in the figure plan.
Source provenance
Decision snapshot
723 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 math-figure-generator, ready for a manual X post.
math-figure-generator: Generate and render-verify publication-quality mathematical-modeling figures from saved evide... 723 stars https://www.openagentskill.com/skills/zhnnky329-math-figure-generator?ref=x
Listing + install path for math-figure-generator: https://www.openagentskill.com/skills/zhnnky329-math-figure-generator?ref=x Install: npx skills add zhnnky329/MathModeling-skills --skill math-figure-generator
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 zhnnky329 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/zhnnky329-math-figure-generator?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/zhnnky329-math-figure-generator?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/zhnnky329-math-figure-generator/audit)
[](https://www.openagentskill.com/skills/zhnnky329-math-figure-generator?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)zhnnky329
@zhnnky329
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Sandbox only
mono-color
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
1.9K StarsLast30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
61.0K StarsAcademic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
38.4K StarsGPT Researcher
Run autonomous deep research over web and local sources
28.0K StarsSandbox only
Install targets
Codex install prompt
Install the "math-figure-generator" agent skill from https://github.com/zhnnky329/MathModeling-skills/tree/main/.claude/skills/math-figure-generator. 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: Generate and render-verify publication-quality mathematical-modeling figures from saved evidence, using the approved figure plan, source data, claim, type, and consistent visual system. 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":"zhnnky329-math-figure-generator","task":"Install math-figure-generator","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.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add zhnnky329/MathModeling-skills --skill math-figure-generator
Maintenance
fresh
12d since push
Risk
Needs review
SKILL.md does not define the meaning of 'Type 3' and 'Type 1/2/4' claims, which may be unclear to users outside the original project context.
GitHub quality
723
75/100 Quality · 74/100 Trust
Coverage tags
Review notes
SKILL.md does not define the meaning of 'Type 3' and 'Type 1/2/4' claims, which may be unclear to users outside the original project context. · No explicit limitations or safe operating boundaries are described in SKILL.md, such as acceptable input formats or behavior when source data is missing or invalid.
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
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
723 GitHub stars
Repo activity
723 stars, 32 forks
Maintenance
12d since push
License
MIT
Install
npx skills add zhnnky329/MathModeling-skills --skill math-figure-generator
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 zhnnky329/MathModeling-skills --skill math-figure-generatorDo not use when
Alternative
1.9K Stars
npx skills add yanliudesign/mono-color-skill --skill mono-color
Alternative
61.0K Stars
npx skills add mvanhorn/last30days-skill -g
Alternative
38.4K Stars
npx skills add Imbad0202/academic-research-skills
Alternative
28.0K Stars
npx skills add assafelovic/gpt-researcher
Agent safety v2
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
medium
Skill may drive a browser or interact with web pages.
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%20math-figure-generator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20math-figure-generator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/zhnnky329-math-figure-generator/install
Agent should check
Copy prompt
Task: Use math-figure-generator in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20math-figure-generator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/zhnnky329-math-figure-generator/install
Install command: npx skills add zhnnky329/MathModeling-skills --skill math-figure-generator
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/zhnnky329-math-figure-generator/install
LLM text format
/api/skills/zhnnky329-math-figure-generator/install?format=text
Find alternatives
/api/skills/search?q=math-figure-generator&limit=3
Agent prompt
Use math-figure-generator for this task. Review https://www.openagentskill.com/api/skills/zhnnky329-math-figure-generator/install, then install with: npx skills add zhnnky329/MathModeling-skills --skill math-figure-generatorRegistry 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/zhnnky329-math-figure-generator
LLM text
/api/registry/manifest/zhnnky329-math-figure-generator?format=text
Install alias
/api/registry/install/zhnnky329-math-figure-generator
Recommend
/api/registry/recommend?task=Use%20math-figure-generator%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Research agents
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO723 GitHub stars
Stars/forks activity
INFO723 stars, 32 forks; issue activity unavailable in current metadata
Recent maintenance
PASS12d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
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.
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Workflow fit
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Alternative shortlist
Similar skills that may fit this task.
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills for Claude Code: research → write → review → revise → finalize
Run autonomous deep research over web and local sources
--- name: math-figure-generator description: Generate and render-verify publication-quality mathematical-modeling figures from saved evidence, using the approved figure plan, source data, claim, type, and consistent visual system. ---
# Preconditions
- Figure type, source artifacts, and target claim are known. - Type 3 claim is human-confirmed. - Submission figures use final/frozen evidence.
# References
Load only what the requested chart needs:
- `references/chart-patterns.md` - `references/color-systems.md` - `references/layout-guide.md` - `references/render-check.md`
# Workflow
1. Verify source files and the exact variables/units to plot. 2. Choose the smallest chart form that communicates the claim. 3. Generate with deterministic code, preferably matplotlib. 4. Save editable source code and the requested output format. 5. Apply the shared color, typography, sizing, and labeling conventions. 6. Render the final output and inspect it visually. 7. Check clipping, overlap, illegible text, misleading axes, legends, empty panels, and source/claim mismatch. 8. Iterate until render checks pass.
# Output Locations
- Type 1/2 exploration: `results/Qx/experiments/roundN/figures/` - Type 3/4 submission: `paper/figures/`
Use stable descriptive filenames. Do not copy Type 1 diagnostics into the paper directory.
# Figure Requirements
- Labels include units where applicable. - Captions state what is shown and the evidence-backed takeaway without overstating causality. - Baseline is visually distinct but not exaggerated. - Uncertainty is shown when it is part of the claim. - Type 3 raster output is at least 300 dpi; vector output is preferred when compatible. - Accessibility and grayscale differentiation are considered.
# Rules
- Do not fabricate or manually alter plotted values. - Do not use a chart type that hides concentration, uncertainty, or negative results. - Do not truncate axes misleadingly. - Do not create decorative 3D effects. - Do not treat code execution as render verification. - Keep diagnostic and paper roles separate.
# Verification
- Source, claim, type, and target section agree. - Render inspection passed. - Text is readable at final paper size. - Legends, colors, markers, axes, units, and captions are consistent. - Final output path exists and is recorded in the figure plan.
Source provenance
Decision snapshot
723 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 math-figure-generator, ready for a manual X post.
math-figure-generator: Generate and render-verify publication-quality mathematical-modeling figures from saved evide... 723 stars https://www.openagentskill.com/skills/zhnnky329-math-figure-generator?ref=x
Listing + install path for math-figure-generator: https://www.openagentskill.com/skills/zhnnky329-math-figure-generator?ref=x Install: npx skills add zhnnky329/MathModeling-skills --skill math-figure-generator
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 zhnnky329 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/zhnnky329-math-figure-generator?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/zhnnky329-math-figure-generator?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/zhnnky329-math-figure-generator/audit)
[](https://www.openagentskill.com/skills/zhnnky329-math-figure-generator?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)zhnnky329
@zhnnky329
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Sandbox only
mono-color
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
1.9K StarsLast30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
61.0K StarsAcademic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
38.4K StarsGPT Researcher
Run autonomous deep research over web and local sources
28.0K StarsPermission surface
no high-risk permission surface in public metadata
Agent outcomes
No agent outcome data yet
Docs
Usable metadata, review docs
Risk summary
Install readiness
Permission surface
no high-risk permission surface in public metadata
Agent outcomes
No agent outcome data yet
Docs
Usable metadata, review docs
Risk summary
Install readiness
Permission surface
no high-risk permission surface in public metadata
Agent outcomes
No agent outcome data yet
Docs
Usable metadata, review docs
Risk summary
Install readiness
Permission surface
no high-risk permission surface in public metadata
Agent outcomes
No agent outcome data yet
Docs
Usable metadata, review docs
Risk summary
Install readiness