/research -- Investigate a topic

SkillDev tools

Execute a multi-pass research investigation, adding claims with evidence.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the /research -- Investigate a topic skill

What this skill tells your AI

The instructions your AI receives, as published by grainulation/grainulator in skills/research/SKILL.md and read by ahel’s review.

The user wants to research a topic within the current sprint.

Arguments

$ARGUMENTS

Instructions

  1. Identify the active sprint by checking for claims.json in the project root, or ask which sprint to target if none exists.

  2. Plan research passes (2-4 passes depending on topic breadth):

    • Pass 1: Broad landscape -- what exists, key concepts, major players
    • Pass 2: Deep dive -- technical details, implementation specifics
    • Pass 3: Risk and trade-offs -- failure modes, limitations, alternatives
    • Pass 4 (if needed): Synthesis -- cross-cutting insights, recommendations
  3. For each pass:

    • Use WebSearch and WebFetch for general research
    • When the user references a GitHub repo or the current repo is on GitHub, use DeepWiki tools to gather codebase context
    • For private repos, use Read/Grep/Glob to analyze code directly
    • Add 3-5 claims per pass via wheat_add-claim:
      • Use r### ID prefix
      • Set appropriate evidence tier (web, documented, tested)
      • Include source URLs in source.artifact when available
      • Mix claim types: factual, estimate, risk, recommendation
    • Run wheat_compile after each pass
    • Announce progress: "Pass 2/3 complete: 11 claims across 4 topics."
  4. Completion check: After all passes, run wheat_status.

    • If total_claims >= 8 and the user's original message included words like "write up", "summarize", "brief", or "report", immediately run the /brief workflow.
    • Otherwise, suggest next steps.
  5. Print summary:

    Research complete: <pass_count> passes, <claim_count> claims across <topic_count> topics.
    
    Next steps:
      /brief              -- generate a compiled brief
      /challenge r003     -- stress-test a specific finding
      /witness r005 <url> -- corroborate with external source
    

Signals

GitHub stars
86
Forks
6
Last commit
Sep 2026
Hacker News mentions
20
Advanced
Catalog kind
skill
Gateway key
research-grainulation
Source
github.com/grainulation/grainulator