Creator · coreyhaines31
Last updated · Sep 2, 2026
When you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a new business idea, positioning angles, due diligence on a partnership or podcast guest, tech decision research (which DB, which auth), or any \"I need to ac
Creator · coreyhaines31
Last updated · Sep 2, 2026
When you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a new business idea, positioning angles, due diligence on a partnership or podcast guest, tech decision research (which DB, which auth), or any \"I need to ac
Creator · coreyhaines31
Last updated · Sep 2, 2026
When you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a new business idea, positioning angles, due diligence on a partnership or podcast guest, tech decision research (which DB, which auth), or any \"I need to ac
Creator · coreyhaines31
Last updated · Sep 2, 2026
When you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a new business idea, positioning angles, due diligence on a partnership or podcast guest, tech decision research (which DB, which auth), or any \"I need to ac
Sandbox only
Install targets
Codex install prompt
Install the "deep-research" agent skill from https://github.com/coreyhaines31/makerskills/tree/main/skills/deep-research. 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: When you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a new business idea, positioning angles, due diligence on a partnership or podcast guest, tech decision research (which DB, which auth), or any \"I need to actually understand X.\" Combines WebSearch, WebFetch, agent-browser, /last30days (Reddit/X/YouTube/HN/web recency), memory, and Notion. Outputs a structured brief with citations, contradictions, gaps, and recommended next steps. Archives every research run to ~/.config/makerskills/deep-research/archive/ so past work is searchable. Triggers on \"/deep-research,\" \"research X,\" \"investigate X,\" \"do a deep dive on X,\" \"look into X,\" \"what's actually happening with X,\" \"due diligence on X,\" \"validate this market.\" Differs from a one-shot WebSearch: this is multi-pass with verification. 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":"coreyhaines31-deep-research","task":"Install deep-research","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 + Browser agents + CLI
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add coreyhaines31/makerskills --skill deep-research
Maintenance
fresh
9d since push
Risk
Needs review
Permission surface may require sandboxing
GitHub quality
755
75/100 Quality · 80/100 Trust
Coverage tags
Review notes
Permission surface may require sandboxing · Financial research output is not financial advice; require human review before any live investment decision
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
755 GitHub stars
Repo activity
755 stars, 62 forks
Maintenance
9d since push
License
MIT
Install
npx skills add coreyhaines31/makerskills --skill deep-research
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 coreyhaines31/makerskills --skill deep-researchDo not use when
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npx skills add mvanhorn/last30days-skill -g
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npx skills add Imbad0202/academic-research-skills
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28.0K Stars
npx skills add assafelovic/gpt-researcher
Agent safety v2
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
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.
high
Skill metadata references credentials, tokens, environment variables, or secret-bearing workflows.
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%20deep-research%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20deep-research%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/coreyhaines31-deep-research/install
Agent should check
Copy prompt
Task: Use deep-research in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20deep-research%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/coreyhaines31-deep-research/install
Install command: npx skills add coreyhaines31/makerskills --skill deep-research
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/coreyhaines31-deep-research/install
LLM text format
/api/skills/coreyhaines31-deep-research/install?format=text
Find alternatives
/api/skills/search?q=deep-research&limit=3
Agent prompt
Use deep-research for this task. Review https://www.openagentskill.com/api/skills/coreyhaines31-deep-research/install, then install with: npx skills add coreyhaines31/makerskills --skill deep-researchRegistry 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/coreyhaines31-deep-research
LLM text
/api/registry/manifest/coreyhaines31-deep-research?format=text
Install alias
/api/registry/install/coreyhaines31-deep-research
Recommend
/api/registry/recommend?task=Use%20deep-research%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code, Browser agents
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
INFO755 GitHub stars
Stars/forks activity
INFO755 stars, 62 forks; issue activity unavailable in current metadata
Recent maintenance
PASS9d 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.
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Workflow fit
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Scrape, clean, and reuse web data
A practical workflow for agents that crawl public pages, extract clean content, normalize data, and hand it to downstream research or RAG workflows.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Alternative shortlist
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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: deep-research description: "When you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a new business idea, positioning angles, due diligence on a partnership or podcast guest, tech decision research (which DB, which auth), or any \"I need to actually understand X.\" Combines WebSearch, WebFetch, agent-browser, /last30days (Reddit/X/YouTube/HN/web recency), memory, and Notion. Outputs a structured brief with citations, contradictions, gaps, and recommended next steps. Archives every research run to ~/.config/makerskills/deep-research/archive/ so past work is searchable. Triggers on \"/deep-research,\" \"research X,\" \"investigate X,\" \"do a deep dive on X,\" \"look into X,\" \"what's actually happening with X,\" \"due diligence on X,\" \"validate this market.\" Differs from a one-shot WebSearch: this is multi-pass with verification." metadata: version: 0.2.0 ---
# /deep-research — Multi-source research with archive
Plans, executes, and synthesizes research from multiple sources. Archives the output so the corpus compounds.
## Step 1 — Frame the question
Restate the research question in one tight sentence. If ambiguous, ask the user: - What's the decision this research will inform? - What's the minimum useful answer? (Saves over-researching.) - Any sources to prioritize or avoid?
Output: `**Research question:** <one sentence>`
## Step 2 — Plan the sources
Pick from this menu based on the question type. Note which sources you'll hit and why.
| Source | When to use | Tool | |---|---|---| | Web search (Google) | Authoritative articles, docs, official statements | `WebSearch` | | `/last30days` | What people are *actually saying* right now — Reddit, X, YouTube, HN, web recency | `Skill({skill: "last30days", args: "<topic>"})` | | Specific URLs | When the user hands over starting URLs | `WebFetch` | | Browsable pages (auth-walled, JS-heavy) | Pricing pages, product tours, profiles | `agent-browser` via the `compound-engineering:agent-browser` skill | | Memory | Prior research / decisions / context the user already captured | grep `~/.claude/memory/` | | Notion | If the topic touches a known Notion workspace | Direct Notion API (key in `$NOTION_API_KEY`, see `reference_notion_api.md`) | | Research archive | Prior `/deep-research` runs that touched this topic | grep `${MAKERSKILLS_CONFIG:-$HOME/.config/makerskills}/deep-research/archive/` |
Run discovery passes **in parallel** where possible. Sequential only when one source needs another's output (e.g., agent-browser a URL discovered by WebSearch).
## Step 3 — Execute discovery
Run each chosen source. For each result, capture: - The source (URL or system) - 1–3 sentence summary of what was said - Date / recency - Confidence in the source (high/medium/low)
Don't synthesize yet — just collect.
## Step 4 — Synthesize
1. **Group findings** by theme or sub-question 2. **Contradiction check** — flag anywhere sources disagree. Don't average them; surface the disagreement. 3. **Confidence**: high (multiple independent sources agree), medium (one strong source or several weak), low (single anecdote or speculation) 4. **Gaps**: what would change the answer? What's NOT in the corpus?
## Step 5 — Output the brief
Use this template:
```markdown # Research: <question>
**Date:** <YYYY-MM-DD> **Decision this informs:** <one line> **Confidence overall:** high / medium / low
## TL;DR <2–4 sentences with the answer>
## Key findings
### 1. <Finding> <2–4 sentences>. Sources: [1], [3], [5]
### 2. <Finding> ...
## Contradictions / uncertainty - <where sources disagree, with each side cited>
## Gaps - <what's missing from the corpus> - <what to research next to close the gap>
## Recommended next steps 1. <action> 2. <action>
## Sources [1] <Title> — <URL or system> (<date>) — <confidence> [2] ... ```
## Step 6 — Archive
Archives live in `${MAKERSKILLS_CONFIG:-$HOME/.config/makerskills}/deep-research/archive/` (create the directory if missing). Never write archives inside the skill's own folder — skill installs and upgrades re-sync from source and wipe anything saved there. **Migration:** if this skill's folder contains an old `references/research-archive/` with user entries, move those files into the archive directory first.
Write the brief to `<archive dir>/<YYYY-MM-DD>-<slug>.md` so it's grep-able forever. Slug = kebab-case of the topic.
Also append a one-line entry to `<archive dir>/INDEX.md` (create if missing):
```markdown - 2026-06-15 — [<topic>](./<filename>.md) — <one-line TL;DR> ```
## Step 7 — Surface
After archiving: - Show the full brief in chat - Tell the user the archive path - Offer: *"Push to Notion or save to a project's docs?"*
## Composes with
- `business-brainstorm` — calls this skill during the market validation step - `/domain` — when research includes "is the .com available" - `/last30days` — one of the data sources
## Notes on quality
- **Always cite.** Every claim in the brief needs a source pointer. - **Recency matters** — note dates on each source. For fast-moving topics (AI, startups), de-weight sources >12 months old. - **Don't trust a single source** for high-stakes claims. Re-search until you have at least 2 independent corroborations or surface the uncertainty. - **No padding.** If the answer is one paragraph, return one paragraph. The template is a maximum, not a minimum.
Source provenance
Decision snapshot
755 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 deep-research, ready for a manual X post.
A practical pick for market research: deep-research: When you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a... 755 stars https://www.openagentskill.com/skills/coreyhaines31-deep-research?ref=x
Listing + install path for deep-research: https://www.openagentskill.com/skills/coreyhaines31-deep-research?ref=x Install: npx skills add coreyhaines31/makerskills --skill deep-research
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 coreyhaines31 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.
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@coreyhaines31
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Install targets
Codex install prompt
Install the "deep-research" agent skill from https://github.com/coreyhaines31/makerskills/tree/main/skills/deep-research. 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: When you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a new business idea, positioning angles, due diligence on a partnership or podcast guest, tech decision research (which DB, which auth), or any \"I need to actually understand X.\" Combines WebSearch, WebFetch, agent-browser, /last30days (Reddit/X/YouTube/HN/web recency), memory, and Notion. Outputs a structured brief with citations, contradictions, gaps, and recommended next steps. Archives every research run to ~/.config/makerskills/deep-research/archive/ so past work is searchable. Triggers on \"/deep-research,\" \"research X,\" \"investigate X,\" \"do a deep dive on X,\" \"look into X,\" \"what's actually happening with X,\" \"due diligence on X,\" \"validate this market.\" Differs from a one-shot WebSearch: this is multi-pass with verification. 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":"coreyhaines31-deep-research","task":"Install deep-research","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 + Browser agents + CLI
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add coreyhaines31/makerskills --skill deep-research
Maintenance
fresh
9d since push
Risk
Needs review
Permission surface may require sandboxing
GitHub quality
755
75/100 Quality · 80/100 Trust
Coverage tags
Review notes
Permission surface may require sandboxing · Financial research output is not financial advice; require human review before any live investment decision
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
755 GitHub stars
Repo activity
755 stars, 62 forks
Maintenance
9d since push
License
MIT
Install
npx skills add coreyhaines31/makerskills --skill deep-research
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 coreyhaines31/makerskills --skill deep-researchDo not use when
Alternative
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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
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
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.
high
Skill metadata references credentials, tokens, environment variables, or secret-bearing workflows.
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%20deep-research%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20deep-research%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/coreyhaines31-deep-research/install
Agent should check
Copy prompt
Task: Use deep-research in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20deep-research%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/coreyhaines31-deep-research/install
Install command: npx skills add coreyhaines31/makerskills --skill deep-research
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/coreyhaines31-deep-research/install
LLM text format
/api/skills/coreyhaines31-deep-research/install?format=text
Find alternatives
/api/skills/search?q=deep-research&limit=3
Agent prompt
Use deep-research for this task. Review https://www.openagentskill.com/api/skills/coreyhaines31-deep-research/install, then install with: npx skills add coreyhaines31/makerskills --skill deep-researchRegistry 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/coreyhaines31-deep-research
LLM text
/api/registry/manifest/coreyhaines31-deep-research?format=text
Install alias
/api/registry/install/coreyhaines31-deep-research
Recommend
/api/registry/recommend?task=Use%20deep-research%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code, Browser agents
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
INFO755 GitHub stars
Stars/forks activity
INFO755 stars, 62 forks; issue activity unavailable in current metadata
Recent maintenance
PASS9d 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.
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Workflow fit
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Scrape, clean, and reuse web data
A practical workflow for agents that crawl public pages, extract clean content, normalize data, and hand it to downstream research or RAG workflows.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
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: deep-research description: "When you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a new business idea, positioning angles, due diligence on a partnership or podcast guest, tech decision research (which DB, which auth), or any \"I need to actually understand X.\" Combines WebSearch, WebFetch, agent-browser, /last30days (Reddit/X/YouTube/HN/web recency), memory, and Notion. Outputs a structured brief with citations, contradictions, gaps, and recommended next steps. Archives every research run to ~/.config/makerskills/deep-research/archive/ so past work is searchable. Triggers on \"/deep-research,\" \"research X,\" \"investigate X,\" \"do a deep dive on X,\" \"look into X,\" \"what's actually happening with X,\" \"due diligence on X,\" \"validate this market.\" Differs from a one-shot WebSearch: this is multi-pass with verification." metadata: version: 0.2.0 ---
# /deep-research — Multi-source research with archive
Plans, executes, and synthesizes research from multiple sources. Archives the output so the corpus compounds.
## Step 1 — Frame the question
Restate the research question in one tight sentence. If ambiguous, ask the user: - What's the decision this research will inform? - What's the minimum useful answer? (Saves over-researching.) - Any sources to prioritize or avoid?
Output: `**Research question:** <one sentence>`
## Step 2 — Plan the sources
Pick from this menu based on the question type. Note which sources you'll hit and why.
| Source | When to use | Tool | |---|---|---| | Web search (Google) | Authoritative articles, docs, official statements | `WebSearch` | | `/last30days` | What people are *actually saying* right now — Reddit, X, YouTube, HN, web recency | `Skill({skill: "last30days", args: "<topic>"})` | | Specific URLs | When the user hands over starting URLs | `WebFetch` | | Browsable pages (auth-walled, JS-heavy) | Pricing pages, product tours, profiles | `agent-browser` via the `compound-engineering:agent-browser` skill | | Memory | Prior research / decisions / context the user already captured | grep `~/.claude/memory/` | | Notion | If the topic touches a known Notion workspace | Direct Notion API (key in `$NOTION_API_KEY`, see `reference_notion_api.md`) | | Research archive | Prior `/deep-research` runs that touched this topic | grep `${MAKERSKILLS_CONFIG:-$HOME/.config/makerskills}/deep-research/archive/` |
Run discovery passes **in parallel** where possible. Sequential only when one source needs another's output (e.g., agent-browser a URL discovered by WebSearch).
## Step 3 — Execute discovery
Run each chosen source. For each result, capture: - The source (URL or system) - 1–3 sentence summary of what was said - Date / recency - Confidence in the source (high/medium/low)
Don't synthesize yet — just collect.
## Step 4 — Synthesize
1. **Group findings** by theme or sub-question 2. **Contradiction check** — flag anywhere sources disagree. Don't average them; surface the disagreement. 3. **Confidence**: high (multiple independent sources agree), medium (one strong source or several weak), low (single anecdote or speculation) 4. **Gaps**: what would change the answer? What's NOT in the corpus?
## Step 5 — Output the brief
Use this template:
```markdown # Research: <question>
**Date:** <YYYY-MM-DD> **Decision this informs:** <one line> **Confidence overall:** high / medium / low
## TL;DR <2–4 sentences with the answer>
## Key findings
### 1. <Finding> <2–4 sentences>. Sources: [1], [3], [5]
### 2. <Finding> ...
## Contradictions / uncertainty - <where sources disagree, with each side cited>
## Gaps - <what's missing from the corpus> - <what to research next to close the gap>
## Recommended next steps 1. <action> 2. <action>
## Sources [1] <Title> — <URL or system> (<date>) — <confidence> [2] ... ```
## Step 6 — Archive
Archives live in `${MAKERSKILLS_CONFIG:-$HOME/.config/makerskills}/deep-research/archive/` (create the directory if missing). Never write archives inside the skill's own folder — skill installs and upgrades re-sync from source and wipe anything saved there. **Migration:** if this skill's folder contains an old `references/research-archive/` with user entries, move those files into the archive directory first.
Write the brief to `<archive dir>/<YYYY-MM-DD>-<slug>.md` so it's grep-able forever. Slug = kebab-case of the topic.
Also append a one-line entry to `<archive dir>/INDEX.md` (create if missing):
```markdown - 2026-06-15 — [<topic>](./<filename>.md) — <one-line TL;DR> ```
## Step 7 — Surface
After archiving: - Show the full brief in chat - Tell the user the archive path - Offer: *"Push to Notion or save to a project's docs?"*
## Composes with
- `business-brainstorm` — calls this skill during the market validation step - `/domain` — when research includes "is the .com available" - `/last30days` — one of the data sources
## Notes on quality
- **Always cite.** Every claim in the brief needs a source pointer. - **Recency matters** — note dates on each source. For fast-moving topics (AI, startups), de-weight sources >12 months old. - **Don't trust a single source** for high-stakes claims. Re-search until you have at least 2 independent corroborations or surface the uncertainty. - **No padding.** If the answer is one paragraph, return one paragraph. The template is a maximum, not a minimum.
Source provenance
Decision snapshot
755 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 deep-research, ready for a manual X post.
A practical pick for market research: deep-research: When you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a... 755 stars https://www.openagentskill.com/skills/coreyhaines31-deep-research?ref=x
Listing + install path for deep-research: https://www.openagentskill.com/skills/coreyhaines31-deep-research?ref=x Install: npx skills add coreyhaines31/makerskills --skill deep-research
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[](https://www.openagentskill.com/skills/coreyhaines31-deep-research?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)coreyhaines31
@coreyhaines31
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 "deep-research" agent skill from https://github.com/coreyhaines31/makerskills/tree/main/skills/deep-research. 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: When you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a new business idea, positioning angles, due diligence on a partnership or podcast guest, tech decision research (which DB, which auth), or any \"I need to actually understand X.\" Combines WebSearch, WebFetch, agent-browser, /last30days (Reddit/X/YouTube/HN/web recency), memory, and Notion. Outputs a structured brief with citations, contradictions, gaps, and recommended next steps. Archives every research run to ~/.config/makerskills/deep-research/archive/ so past work is searchable. Triggers on \"/deep-research,\" \"research X,\" \"investigate X,\" \"do a deep dive on X,\" \"look into X,\" \"what's actually happening with X,\" \"due diligence on X,\" \"validate this market.\" Differs from a one-shot WebSearch: this is multi-pass with verification. 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":"coreyhaines31-deep-research","task":"Install deep-research","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 + Browser agents + CLI
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add coreyhaines31/makerskills --skill deep-research
Maintenance
fresh
9d since push
Risk
Needs review
Permission surface may require sandboxing
GitHub quality
755
75/100 Quality · 80/100 Trust
Coverage tags
Review notes
Permission surface may require sandboxing · Financial research output is not financial advice; require human review before any live investment decision
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
755 GitHub stars
Repo activity
755 stars, 62 forks
Maintenance
9d since push
License
MIT
Install
npx skills add coreyhaines31/makerskills --skill deep-research
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 coreyhaines31/makerskills --skill deep-researchDo not use when
Alternative
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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
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
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.
high
Skill metadata references credentials, tokens, environment variables, or secret-bearing workflows.
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%20deep-research%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20deep-research%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/coreyhaines31-deep-research/install
Agent should check
Copy prompt
Task: Use deep-research in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20deep-research%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/coreyhaines31-deep-research/install
Install command: npx skills add coreyhaines31/makerskills --skill deep-research
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/coreyhaines31-deep-research/install
LLM text format
/api/skills/coreyhaines31-deep-research/install?format=text
Find alternatives
/api/skills/search?q=deep-research&limit=3
Agent prompt
Use deep-research for this task. Review https://www.openagentskill.com/api/skills/coreyhaines31-deep-research/install, then install with: npx skills add coreyhaines31/makerskills --skill deep-researchRegistry 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/coreyhaines31-deep-research
LLM text
/api/registry/manifest/coreyhaines31-deep-research?format=text
Install alias
/api/registry/install/coreyhaines31-deep-research
Recommend
/api/registry/recommend?task=Use%20deep-research%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code, Browser agents
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
INFO755 GitHub stars
Stars/forks activity
INFO755 stars, 62 forks; issue activity unavailable in current metadata
Recent maintenance
PASS9d 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.
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Workflow fit
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Scrape, clean, and reuse web data
A practical workflow for agents that crawl public pages, extract clean content, normalize data, and hand it to downstream research or RAG workflows.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
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: deep-research description: "When you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a new business idea, positioning angles, due diligence on a partnership or podcast guest, tech decision research (which DB, which auth), or any \"I need to actually understand X.\" Combines WebSearch, WebFetch, agent-browser, /last30days (Reddit/X/YouTube/HN/web recency), memory, and Notion. Outputs a structured brief with citations, contradictions, gaps, and recommended next steps. Archives every research run to ~/.config/makerskills/deep-research/archive/ so past work is searchable. Triggers on \"/deep-research,\" \"research X,\" \"investigate X,\" \"do a deep dive on X,\" \"look into X,\" \"what's actually happening with X,\" \"due diligence on X,\" \"validate this market.\" Differs from a one-shot WebSearch: this is multi-pass with verification." metadata: version: 0.2.0 ---
# /deep-research — Multi-source research with archive
Plans, executes, and synthesizes research from multiple sources. Archives the output so the corpus compounds.
## Step 1 — Frame the question
Restate the research question in one tight sentence. If ambiguous, ask the user: - What's the decision this research will inform? - What's the minimum useful answer? (Saves over-researching.) - Any sources to prioritize or avoid?
Output: `**Research question:** <one sentence>`
## Step 2 — Plan the sources
Pick from this menu based on the question type. Note which sources you'll hit and why.
| Source | When to use | Tool | |---|---|---| | Web search (Google) | Authoritative articles, docs, official statements | `WebSearch` | | `/last30days` | What people are *actually saying* right now — Reddit, X, YouTube, HN, web recency | `Skill({skill: "last30days", args: "<topic>"})` | | Specific URLs | When the user hands over starting URLs | `WebFetch` | | Browsable pages (auth-walled, JS-heavy) | Pricing pages, product tours, profiles | `agent-browser` via the `compound-engineering:agent-browser` skill | | Memory | Prior research / decisions / context the user already captured | grep `~/.claude/memory/` | | Notion | If the topic touches a known Notion workspace | Direct Notion API (key in `$NOTION_API_KEY`, see `reference_notion_api.md`) | | Research archive | Prior `/deep-research` runs that touched this topic | grep `${MAKERSKILLS_CONFIG:-$HOME/.config/makerskills}/deep-research/archive/` |
Run discovery passes **in parallel** where possible. Sequential only when one source needs another's output (e.g., agent-browser a URL discovered by WebSearch).
## Step 3 — Execute discovery
Run each chosen source. For each result, capture: - The source (URL or system) - 1–3 sentence summary of what was said - Date / recency - Confidence in the source (high/medium/low)
Don't synthesize yet — just collect.
## Step 4 — Synthesize
1. **Group findings** by theme or sub-question 2. **Contradiction check** — flag anywhere sources disagree. Don't average them; surface the disagreement. 3. **Confidence**: high (multiple independent sources agree), medium (one strong source or several weak), low (single anecdote or speculation) 4. **Gaps**: what would change the answer? What's NOT in the corpus?
## Step 5 — Output the brief
Use this template:
```markdown # Research: <question>
**Date:** <YYYY-MM-DD> **Decision this informs:** <one line> **Confidence overall:** high / medium / low
## TL;DR <2–4 sentences with the answer>
## Key findings
### 1. <Finding> <2–4 sentences>. Sources: [1], [3], [5]
### 2. <Finding> ...
## Contradictions / uncertainty - <where sources disagree, with each side cited>
## Gaps - <what's missing from the corpus> - <what to research next to close the gap>
## Recommended next steps 1. <action> 2. <action>
## Sources [1] <Title> — <URL or system> (<date>) — <confidence> [2] ... ```
## Step 6 — Archive
Archives live in `${MAKERSKILLS_CONFIG:-$HOME/.config/makerskills}/deep-research/archive/` (create the directory if missing). Never write archives inside the skill's own folder — skill installs and upgrades re-sync from source and wipe anything saved there. **Migration:** if this skill's folder contains an old `references/research-archive/` with user entries, move those files into the archive directory first.
Write the brief to `<archive dir>/<YYYY-MM-DD>-<slug>.md` so it's grep-able forever. Slug = kebab-case of the topic.
Also append a one-line entry to `<archive dir>/INDEX.md` (create if missing):
```markdown - 2026-06-15 — [<topic>](./<filename>.md) — <one-line TL;DR> ```
## Step 7 — Surface
After archiving: - Show the full brief in chat - Tell the user the archive path - Offer: *"Push to Notion or save to a project's docs?"*
## Composes with
- `business-brainstorm` — calls this skill during the market validation step - `/domain` — when research includes "is the .com available" - `/last30days` — one of the data sources
## Notes on quality
- **Always cite.** Every claim in the brief needs a source pointer. - **Recency matters** — note dates on each source. For fast-moving topics (AI, startups), de-weight sources >12 months old. - **Don't trust a single source** for high-stakes claims. Re-search until you have at least 2 independent corroborations or surface the uncertainty. - **No padding.** If the answer is one paragraph, return one paragraph. The template is a maximum, not a minimum.
Source provenance
Decision snapshot
755 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 deep-research, ready for a manual X post.
A practical pick for market research: deep-research: When you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a... 755 stars https://www.openagentskill.com/skills/coreyhaines31-deep-research?ref=x
Listing + install path for deep-research: https://www.openagentskill.com/skills/coreyhaines31-deep-research?ref=x Install: npx skills add coreyhaines31/makerskills --skill deep-research
Listing source
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Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
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Creator backlink kit
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@coreyhaines31
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 "deep-research" agent skill from https://github.com/coreyhaines31/makerskills/tree/main/skills/deep-research. 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: When you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a new business idea, positioning angles, due diligence on a partnership or podcast guest, tech decision research (which DB, which auth), or any \"I need to actually understand X.\" Combines WebSearch, WebFetch, agent-browser, /last30days (Reddit/X/YouTube/HN/web recency), memory, and Notion. Outputs a structured brief with citations, contradictions, gaps, and recommended next steps. Archives every research run to ~/.config/makerskills/deep-research/archive/ so past work is searchable. Triggers on \"/deep-research,\" \"research X,\" \"investigate X,\" \"do a deep dive on X,\" \"look into X,\" \"what's actually happening with X,\" \"due diligence on X,\" \"validate this market.\" Differs from a one-shot WebSearch: this is multi-pass with verification. 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":"coreyhaines31-deep-research","task":"Install deep-research","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 + Browser agents + CLI
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add coreyhaines31/makerskills --skill deep-research
Maintenance
fresh
9d since push
Risk
Needs review
Permission surface may require sandboxing
GitHub quality
755
75/100 Quality · 80/100 Trust
Coverage tags
Review notes
Permission surface may require sandboxing · Financial research output is not financial advice; require human review before any live investment decision
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
755 GitHub stars
Repo activity
755 stars, 62 forks
Maintenance
9d since push
License
MIT
Install
npx skills add coreyhaines31/makerskills --skill deep-research
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 coreyhaines31/makerskills --skill deep-researchDo not use when
Alternative
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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
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
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.
high
Skill metadata references credentials, tokens, environment variables, or secret-bearing workflows.
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%20deep-research%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20deep-research%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/coreyhaines31-deep-research/install
Agent should check
Copy prompt
Task: Use deep-research in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20deep-research%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/coreyhaines31-deep-research/install
Install command: npx skills add coreyhaines31/makerskills --skill deep-research
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/coreyhaines31-deep-research/install
LLM text format
/api/skills/coreyhaines31-deep-research/install?format=text
Find alternatives
/api/skills/search?q=deep-research&limit=3
Agent prompt
Use deep-research for this task. Review https://www.openagentskill.com/api/skills/coreyhaines31-deep-research/install, then install with: npx skills add coreyhaines31/makerskills --skill deep-researchRegistry 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/coreyhaines31-deep-research
LLM text
/api/registry/manifest/coreyhaines31-deep-research?format=text
Install alias
/api/registry/install/coreyhaines31-deep-research
Recommend
/api/registry/recommend?task=Use%20deep-research%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code, Browser agents
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
INFO755 GitHub stars
Stars/forks activity
INFO755 stars, 62 forks; issue activity unavailable in current metadata
Recent maintenance
PASS9d 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.
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Workflow fit
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Scrape, clean, and reuse web data
A practical workflow for agents that crawl public pages, extract clean content, normalize data, and hand it to downstream research or RAG workflows.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
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: deep-research description: "When you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a new business idea, positioning angles, due diligence on a partnership or podcast guest, tech decision research (which DB, which auth), or any \"I need to actually understand X.\" Combines WebSearch, WebFetch, agent-browser, /last30days (Reddit/X/YouTube/HN/web recency), memory, and Notion. Outputs a structured brief with citations, contradictions, gaps, and recommended next steps. Archives every research run to ~/.config/makerskills/deep-research/archive/ so past work is searchable. Triggers on \"/deep-research,\" \"research X,\" \"investigate X,\" \"do a deep dive on X,\" \"look into X,\" \"what's actually happening with X,\" \"due diligence on X,\" \"validate this market.\" Differs from a one-shot WebSearch: this is multi-pass with verification." metadata: version: 0.2.0 ---
# /deep-research — Multi-source research with archive
Plans, executes, and synthesizes research from multiple sources. Archives the output so the corpus compounds.
## Step 1 — Frame the question
Restate the research question in one tight sentence. If ambiguous, ask the user: - What's the decision this research will inform? - What's the minimum useful answer? (Saves over-researching.) - Any sources to prioritize or avoid?
Output: `**Research question:** <one sentence>`
## Step 2 — Plan the sources
Pick from this menu based on the question type. Note which sources you'll hit and why.
| Source | When to use | Tool | |---|---|---| | Web search (Google) | Authoritative articles, docs, official statements | `WebSearch` | | `/last30days` | What people are *actually saying* right now — Reddit, X, YouTube, HN, web recency | `Skill({skill: "last30days", args: "<topic>"})` | | Specific URLs | When the user hands over starting URLs | `WebFetch` | | Browsable pages (auth-walled, JS-heavy) | Pricing pages, product tours, profiles | `agent-browser` via the `compound-engineering:agent-browser` skill | | Memory | Prior research / decisions / context the user already captured | grep `~/.claude/memory/` | | Notion | If the topic touches a known Notion workspace | Direct Notion API (key in `$NOTION_API_KEY`, see `reference_notion_api.md`) | | Research archive | Prior `/deep-research` runs that touched this topic | grep `${MAKERSKILLS_CONFIG:-$HOME/.config/makerskills}/deep-research/archive/` |
Run discovery passes **in parallel** where possible. Sequential only when one source needs another's output (e.g., agent-browser a URL discovered by WebSearch).
## Step 3 — Execute discovery
Run each chosen source. For each result, capture: - The source (URL or system) - 1–3 sentence summary of what was said - Date / recency - Confidence in the source (high/medium/low)
Don't synthesize yet — just collect.
## Step 4 — Synthesize
1. **Group findings** by theme or sub-question 2. **Contradiction check** — flag anywhere sources disagree. Don't average them; surface the disagreement. 3. **Confidence**: high (multiple independent sources agree), medium (one strong source or several weak), low (single anecdote or speculation) 4. **Gaps**: what would change the answer? What's NOT in the corpus?
## Step 5 — Output the brief
Use this template:
```markdown # Research: <question>
**Date:** <YYYY-MM-DD> **Decision this informs:** <one line> **Confidence overall:** high / medium / low
## TL;DR <2–4 sentences with the answer>
## Key findings
### 1. <Finding> <2–4 sentences>. Sources: [1], [3], [5]
### 2. <Finding> ...
## Contradictions / uncertainty - <where sources disagree, with each side cited>
## Gaps - <what's missing from the corpus> - <what to research next to close the gap>
## Recommended next steps 1. <action> 2. <action>
## Sources [1] <Title> — <URL or system> (<date>) — <confidence> [2] ... ```
## Step 6 — Archive
Archives live in `${MAKERSKILLS_CONFIG:-$HOME/.config/makerskills}/deep-research/archive/` (create the directory if missing). Never write archives inside the skill's own folder — skill installs and upgrades re-sync from source and wipe anything saved there. **Migration:** if this skill's folder contains an old `references/research-archive/` with user entries, move those files into the archive directory first.
Write the brief to `<archive dir>/<YYYY-MM-DD>-<slug>.md` so it's grep-able forever. Slug = kebab-case of the topic.
Also append a one-line entry to `<archive dir>/INDEX.md` (create if missing):
```markdown - 2026-06-15 — [<topic>](./<filename>.md) — <one-line TL;DR> ```
## Step 7 — Surface
After archiving: - Show the full brief in chat - Tell the user the archive path - Offer: *"Push to Notion or save to a project's docs?"*
## Composes with
- `business-brainstorm` — calls this skill during the market validation step - `/domain` — when research includes "is the .com available" - `/last30days` — one of the data sources
## Notes on quality
- **Always cite.** Every claim in the brief needs a source pointer. - **Recency matters** — note dates on each source. For fast-moving topics (AI, startups), de-weight sources >12 months old. - **Don't trust a single source** for high-stakes claims. Re-search until you have at least 2 independent corroborations or surface the uncertainty. - **No padding.** If the answer is one paragraph, return one paragraph. The template is a maximum, not a minimum.
Source provenance
Decision snapshot
755 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 deep-research, ready for a manual X post.
A practical pick for market research: deep-research: When you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a... 755 stars https://www.openagentskill.com/skills/coreyhaines31-deep-research?ref=x
Listing + install path for deep-research: https://www.openagentskill.com/skills/coreyhaines31-deep-research?ref=x Install: npx skills add coreyhaines31/makerskills --skill deep-research
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Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
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@coreyhaines31
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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
filesystem or document access, network or browser access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness
Permission surface
filesystem or document access, network or browser access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness
Permission surface
filesystem or document access, network or browser access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness
Permission surface
filesystem or document access, network or browser access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness