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Research

Skill arendon1/agent-skills/process/research

Gather external knowledge into the active plan's RESEARCH.md so build grounds in facts, not hallucinations. Every finding cites a source. Delegates to domain capabilities (e.g. research-literature for academic) based on their provides field. Use when the plan needs external facts before building, or when the user says "research this", "look up", "find docs on", "is there a library for".From its SKILL.md

Install
npx -y skills add arendon1/agent-skills --skill research

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

5.2 KB, ~1.3k tokens by cl100k_base, as published. Nobody here has run it

research — external knowledge into RESEARCH.md

Gather external knowledge the plan needs and distill it into RESEARCH.md — the durable research log — so build grounds in facts instead of hallucinating library behavior. Every finding cites a source; unsourced claims are flagged, never written as fact.

Process without library context gives you well-organized hallucinations. build invents a plausible-but-wrong API and LESSONS.md fills with avoidable bugs. Research is the external oracle: pull the real fact once, log it in caveman, never re-derive.

OWNERSHIP

Owns: RESEARCH.md in the active plan folder (appends sourced rows). Reads: PRD.md, ARD.md, SPEC.md, CONTEXT.md. Hands off to: spec (if a finding changes a §C constraint or §I interface, note the edit for spec to make). MUST NOT write PRD.md, ARD.md, SPEC.md, PLAN.md, or LESSONS.md.

WHEN (user-invoked)

  • A constraint / interface / invariant decision hinges on a library, API, version, or pattern you are unsure of.
  • You are about to assume how an external dependency behaves.
  • The idea touches a domain with real prior art (auth, payments, crypto, rate-limiting, distributed systems).
  • grill parked a ? that the outside world must answer.
  • User says "research this", "look up", "find docs on", "is there a library for".

Skip when the build touches only code you already wrote. Research scales to the unknown, not to habit.

STEP 0 — READ EXISTING STATE

  1. Resolve the active plan per §6. If none, ask the user to run grill first (research needs a question in scope).
  2. Read PRD.md to find parked ? items and the constraints/interfaces the research must inform.
  3. Read CONTEXT.md for canonical terms.

STEP 1 — SCOPE

Turn the unknown into 1-3 concrete questions. Vague "research auth" becomes: "JWT lib for Node ESM, maintained?" + "refresh-token rotation: current best practice?". A scoped question gets a citable answer; a vague one gets an essay.

STEP 2 — DELEGATE TO DOMAIN CAPABILITIES

If the question falls in a domain a capability skill covers, delegate to it (by the provides: field in the domain skill's frontmatter, per §5):

  • Academic / literature search -> the research-literature skill (provides: [academic-search]).
  • Other domain capabilities as they are added.

If no domain capability fits, gather directly using web search / docs tools.

Prefer primary sources: official docs, the repo, the RFC, the paper. Two independent sources beat one confident blog. For a big sweep, dispatch a subagent (via the dispatch discipline) so the raw pages never touch this context — it returns only the distilled finding + source.

STEP 3 — DISTILL

Crush each answer to one caveman line + its source. Drop the prose. The RESEARCH.md row is the memory; the tab you read is not.

R3|refresh token|rotate on use, revoke family on reuse-detect|datatracker.ietf.org/doc/html/rfc6819#section-5.2.2.3

STEP 4 — WRITE RESEARCH.md + HAND OFF

Append the §R rows to RESEARCH.md using caveman. If a finding changes a constraint or interface, note the §C/§I edit for the spec skill to make. Research proposes; spec writes.

Template for RESEARCH.md:

# RESEARCH — <slug>

## §R FINDINGS

id|topic|finding|source
R1|jwt lib|`jose` > `jsonwebtoken` — maintained, ESM, 0 deps|github.com/panva/jose
R2|rate limit|token bucket ok @ our scale|<url>
R3|refresh token|rotate on use, revoke family on reuse-detect|datatracker.ietf.org/doc/html/rfc6819#section-5.2.2.3

Table cell rules: literal | -> escape as \|. Empty = -.

SOURCE DISCIPLINE

  • Cite a URL, repo, RFC, or paper per row. Verbatim identifiers / versions.
  • Could not verify -> write the row but flag ? in the finding and say so. An unverified claim labeled honestly is fine; one disguised as fact is a future LESSONS.md bug.
  • Conflicting sources -> log both, let the user pick. NEVER silently average them.

WHEN TO STOP

Done when every scoped question has a sourced §R row (or an honest ?), and no build decision still rests on an unchecked assumption. Do not research past the questions you scoped — that is just burning the attention budget.

BOUNDARIES

  • MUST NOT write SPEC.md / PRD.md / ARD.md / PLAN.md / LESSONS.md. Hand §R rows + any §C/§I edit notes to spec.
  • MUST NOT write a finding as fact without a source.
  • MUST NOT dump raw pages into context or RESEARCH.md. Distill or it does not land.
  • MUST NOT research what you can read in the repo. Local truth > web guess.
  • MUST delegate to domain capabilities by their provides field when one fits.
  • MUST use caveman and CONTEXT.md canonical terms.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 0 of the 12 instructions most research analysis skills give in ~1.3k tokens

Counted across 1,063 of the 1,754 authors here whose files we hold, read 2026-08-07

  • Generate a markdown reportin 32 of 1063, across 23 files
  • Cite each claim's sourcein 30 of 1063, across 15 files
  • Define the ideal customer profilein 20 of 1063, across 2 files
  • Search for companies matching the criteriain 20 of 1063, across 2 files
  • Assign a fit score from one to tenin 20 of 1063, across 2 files
  • Analyze the codebase to understand the productin 19 of 1063, across 1 file
  • Ask clarifying questions about the value propositionin 19 of 1063, across 1 file
  • Look for signals of immediate needin 19 of 1063, across 1 file
  • Identify the target decision maker rolein 19 of 1063, across 1 file
  • Suggest a personalized contact strategyin 19 of 1063, across 1 file
  • Provide conversation starters for outreachin 19 of 1063, across 1 file
  • Format results in a scannable markdown templatein 19 of 1063, across 1 file

Said here and by no other author read

  • scope unknowns into concrete questions
  • delegate to domain capabilities when one fits
  • distill each finding to one caveman line
  • cite a source per research row
  • append sourced rows to the research log
  • note spec edits for interface changes

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

Keep looking

Skills are one crate of 326,679. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.