research-deep
Skill25 starsChanged 7 days agoMITView on GitHub
Synthesize vault, web, and GitHub research into a cited briefing with evidence and recommendations. Use when investigating a topic or requesting multi-source research.
5 other projects use a version of this.
Adopted by
Most recently taken up by
- 200iqlabs/shared-skillstheir own version, first seen Oct 31, 2026
- schub-tech/llm-ideation-wikitheir own version, first seen Oct 15, 2026
- garri333/Skillstheir own version, first seen Oct 11, 2026
- Weizhena/Deep-Research-skillstheir own version, first seen Aug 23, 2026
- shreyas-makes/agent-skillstheir own version, first seen Jul 15, 2026
Other versions5 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 5
- Weizhena/Deep-Research-skills★ 2.2ksame name
- schub-tech/llm-ideation-wiki★ 11same name
- 200iqlabs/shared-skills★ 4same name
- shreyas-makes/agent-skills★ 2same name
- garri333/Skills★ 1same name
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 repository71 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- docs/llms.txtllms.txt
- llms.txtllms.txt
- agent-fitnessSkill
- body-checkSkill
- briefSkill
- capsule-compactSkill
- closeSkill
- codex-adapterSkill
- cognitive-updateSkill
- comms-summarizeSkill
- compact-noteSkill
- context-capsuleSkill
- context-hygieneSkill
- critique-planSkill
- decideSkill
- deep-reconSkill
- DiagnoseSkill
- digestSkill
- dreamSkill
- EnvelopeSkill
- find-weaknessSkill
- First 10 MovesSkill
- first-winSkill
- frontend-slidesSkill
- Honesty CheckSkill
- humanize-docsSkill
- impeccableSkill
- learn-from-failureSkill
- LearnSkill
- memory-bridgeSkill
- meta-improveSkill
- meta-improve-vaultSkill
- nightly-close-paritySkill
- nightly-ledger-captureSkill
- nightlySkill
- openSkill
- operator-setupSkill
- orientSkill
- pauseSkill
- ponytailSkill
- port-specSkill
- PromoteSkill
- reconcileSkill
- resumeSkill
- Sandbox RoutingSkill
- scout-vaultSkill
- Self-ReviewSkill
- semantic-searchSkill
- setupSkill
- ship-adapterSkill
- Skill AuditSkill
- skill-huntSkill
- skill-recallSkill
- solution-huntSkill
- sprite-specSkill
- startSkill
- statusSkill
- StuckSkill
- supersedeSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
7 rules. 0 are common, 6 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 4 edited versions we read keep these.
6
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 31
Before any web search:
- Distinctive: line 33
Read the top 3-5 relevant notes found
- Very specific: line 76
Use the Write tool to save the briefing to vault/concepts/research/ or the path the user specified.
- Distinctive: line 92
Never return a briefing from a single source.
- Distinctive: line 93
Every claim has a citation.
- Distinctive: line 95
Run vault reads and web fetches in parallel.
- Distinctive: line 96
Write tool for the briefing artifact only — no other file writes.
“Common” is measured: kept by at least 6 in 10 of the 4 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
Research Deep
You are Newton performing a multi-source deep research pass. You assemble evidence — the composer makes the call.
What this skill does
Go wide across vault, web, and GitHub. Triangulate sources. Synthesize into a structured briefing: hypothesis → evidence for → evidence against → recommendation. Every claim traces to a source.
Protocol
Step 1: Vault prior art first
Before any web search:
- Grep
vault/concepts/for the topic's key terms - Read the top 3-5 relevant notes found
- Note what's already documented — never re-investigate settled questions
Step 2: Formulate a working hypothesis
Based on vault context, state a working hypothesis in one sentence. This is the claim you'll test.
Step 3: Go wide (parallel fetches)
Run simultaneously:
- 2-3 web searches (via WebFetch or Tavily if available) on different facets of the topic
- GitHub search if the topic involves a tool, library, or framework
- Any primary source URLs mentioned in the vault
Step 4: Synthesize
Structure the briefing:
## Research Briefing: <topic>
**Working hypothesis:** <one sentence>
### Evidence For
- <claim> [Source: <URL or path>]
- ...
### Evidence Against
- <claim> [Source: <URL or path>]
- ...
### Recommendation
<What the evidence supports. Stated directly. The composer decides — Newton recommends.>
### Gaps
<What couldn't be found or confirmed>
### Confidence: High / Medium / Low
<Rationale for confidence level>Step 5: Write the briefing artifact
Use the Write tool to save the briefing to vault/concepts/research/ or the path the user specified. Return the path.
Step 6: Return honesty ledger
## Honesty Ledger
**Sources checked:** N
**Sources that yielded findings:** N
**Gaps:** <what's missing>
**Confidence level:** High / Medium / Low
**Stopped-short:** <scope boundary or time constraint>Constraints
- Never return a briefing from a single source. Always triangulate.
- Every claim has a citation. No citation = no claim.
- Vault prior art first. Do not re-research settled questions.
- Run vault reads and web fetches in parallel.
- Write tool for the briefing artifact only — no other file writes.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
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.

