deep-research
Skill0 starsChanged 52 days agoMITView on GitHub
Investigate a question against high-trust primary sources and capture the findings as a Markdown file in the repo. Use when the user wants a topic researched, docs or API facts gathered, or reading legwork delegated to a background agent. Manual tool skill — invoked by name.
196 other projects use a version of this.
Adopted by
Most recently taken up by
- ridelink0/ultimate-frontend-skillstheir own version, first seen Nov 8, 2026
- chrisblattman/claudeblattmantheir own version, first seen Nov 8, 2026
- genericService/claude-skillstheir own version, first seen Nov 8, 2026
- ourostack/ouroboros-skillstheir own version, first seen Nov 8, 2026
- mahsumaktas/agent-evolution-kittheir own version, first seen Nov 8, 2026
- insight68/Skillstheir own version, first seen Nov 8, 2026
Used with
Projects with it also use community-led-growth, ph-community-outreach and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
nicepkgSkillcommunity-led-growth
Expert in community-led growth (CLG) - leveraging user communities to drive acquisition, retention, and expansion. Covers building developer communities, user groups, ambassador programs, and turning customers into advocates. Knows the difference between community as a feature vs community as a growth engine, and how to measure community ROI. Use when "community-led, CLG, ambassador program, champion program, user community, developer community, word of mouth, user group, " mentioned.
Also in 5 projects that use this
nicepkgSkillph-community-outreach
Engage Reddit, Indie Hackers, Hacker News and other communities for Product Hunt launches. Use this skill to identify relevant communities, craft appropriate posts, and drive cross-platform engagement without appearing spammy.
Also in 5 projects that use this
W-MoorerSkillacademic-paper-reviewer
Multi-perspective academic paper review with dynamic reviewer personas. Simulates 5 independent reviewers (EIC + 3 peer reviewers + Devil's Advocate) with field-specific expertise. Supports full review, re-review (verification), quick assessment, methodology focus, Socratic guided, and calibration modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy.
Also in 11 projects that use this
W-MoorerSkillacademic-pipeline
Orchestrator for the full academic research pipeline: research -> write -> integrity check -> review -> revise -> re-review -> re-revise -> final integrity check -> finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 10-stage workflow with mandatory integrity verification, two-stage peer review, and reproducible quality gates. Triggers on: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publication, complete paper workflow.
Also in 10 projects that use this
xfstudioSkillmicro-saas-launcher
Expert in launching small, focused SaaS products fast - the indie hacker approach to building profitable software. Covers idea validation, MVP development, pricing, launch strategies, and growing to sustainable revenue. Ship in weeks, not months. Use when: micro saas, indie hacker, small saas, side project, saas mvp.
Also in 5 projects that use this
stophobiaSkillsurprise-me
Create a delightful, unexpected "wow" experience for the user by dynamically discovering and creatively combining other enabled skills. Triggers when the user says "surprise me" or any request expressing a desire for an unexpected creative showcase. Also triggers when the user is bored, wants inspiration, or asks for "something interesting".
Also in 4 projects that use this
- +4 more from nicepkg
- +1 more from W-Moorer
Other versions196 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 196
- affaan-m/ECC★ 246ksame name
- bytedance/deer-flow★ 85ksame name
- Imbad0202/academic-research-skills★ 56ksame name
- THU-MAIC/OpenMAIC★ 43ksame name
- HKUSTDial/Supervisor-Skills★ 12ksame name
- genspark-ai/genoffice★ 12ksame name
- advaitpaliwal/feynman★ 10ksame name
- companion-inc/feynman★ 10ksame name
- getcompanion-ai/feynman★ 10ksame name
- jordan-gibbs/hyperresearch★ 4.4ksame name
186 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository12 other files it gives its agents.
- authoring-skillsSkill
- completion-gateSkill
- design-interviewSkill
- domain-glossarySkill
- dual-axis-reviewSkill
- finish-handoffSkill
- hypothesis-debuggingSkill
- seam-designSkill
- seam-driven-tddSkill
- tracer-planSkill
- using-waypowerSkill
- waymapSkill
The file
We split this skill into the rules it gives an agent
2 rules. 0 are common, 1 is distinctive, and 1 is very specific to this project.
0
Common
Most of the 177 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 13
Write the findings to a single Markdown file, citing each claim's source.
- Very specific: line 21
When the research answers a design-interview question, hand the file to that interview as input.
“Common” is measured: kept by at least 6 in 10 of the 177 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Deep Research
Spin up a background agent to do the research, so you keep working while it reads.
Its job:
- Investigate the question against primary sources (official docs, source code, specs, first-party APIs), not a secondary write-up of them. Follow every claim back to the source that owns it.
- Write the findings to a single Markdown file, citing each claim's source.
- Save it where the repo already keeps such notes; match the existing convention, and if there is none, put it somewhere sensible and say where.
Doing It Well
- Scope before dispatching: one question per agent. A broad topic becomes several parallel background agents, each with its own file.
- The agent's prompt carries: the question, which sources count as primary for it, where to save, and the citation rule — every claim tagged with the URL or file:line that owns it.
- Findings that feed a design decision are durable artifacts: they belong in
docs/(or the repo's notes convention), not in the issue tracker; tickets and designs reference them by path. - When the research answers a
design-interviewquestion, hand the file to that interview as input. Facts an interview needs are gathered by sub-agents — deep-research is how the heavy reading gets done.
Common Rationalizations
| Excuse | Reality |
| "I know this from training — no need to check" | Training data ages and generalizes; primary sources are current and specific to this version. |
| "A good blog post covers it" | Secondary sources restate primary ones, with drift. Follow the claim to its owner. |
| "Citations are overhead" | An uncited claim can't be re-verified when the answer is challenged. |
| "I'll paste the findings in chat" | Chat scrolls away; the file is the artifact the next session reads. |
Red Flags — STOP
- Answering from memory when the user asked for research
- Citing a source you didn't actually open
- Findings that exist only in chat
Completion Checklist
Feeds completion-gate; never replaces it:
- Background agent(s) dispatched, one scoped question each
- Every claim traced to a primary source and cited
- Findings saved to a Markdown file in the repo's notes convention
- Durable findings referenced by path from any ticket or design that uses them
In Waypower
Manual tool skill; the orchestrator never auto-triggers it. Sibling distinction: design-interview gathers project facts via sub-agents inside its interview; deep-research is user-invoked, standalone, and writes durable files. Research findings often become inputs to design-interview's shared understanding.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

