research

name	research
description	Research external topics, create comprehensive analysis, and incorporate learnings into memory systems
model	opus
allowed-tools	WebSearch, WebFetch, Read, Write, Glob, Grep, Bash(python3:*/skills/github/scripts/*), mcp__forgetful__*, mcp__serena__*, Skill
user-invocable	true

Research and Incorporate Command

ultrathink

Research external topics, create comprehensive analysis, and incorporate learnings into memory systems.

Usage

/research

Topic: {topic name}
Context: {why this matters to the project}
URLs: {optional comma-separated source URLs}

Parameters

Parameter	Required	Description
Topic	Yes	Subject to research
Context	Yes	Why this matters to the project
URLs	No	Source URLs to fetch and analyze

Example

/research

Topic: Chesterton's Fence
Context: Decision-making principle for understanding existing systems before changing them
URLs: https://fs.blog/chestertons-fence/, https://en.wikipedia.org/wiki/G._K._Chesterton

What This Does

1. Research Phase: Check existing knowledge, fetch URLs, perform web searches
2. Analysis Phase: Write 3000-5000 word analysis to .agents/analysis/
3. Applicability Phase: Map integration points with ai-agents project
4. Memory Phase: Create Serena memory + 5-10 atomic Forgetful memories
5. Action Phase: Create GitHub issue if implementation work identified, via python3 "${COPILOT_PLUGIN_ROOT:-${CLAUDE_PLUGIN_ROOT:-.claude}}/skills/github/scripts/issue/new_issue.py"

Budget

Complete within 50k output tokens. If approaching the limit, summarize findings so far, persist partial analysis, and stop. Prefer completing fewer phases well over partial work across all phases.

Fallback Rules

• If WebSearch returns no results for a query, try 2 alternative phrasings, then proceed with available information.
• If a WebFetch URL is unreachable or returns a non-success status, note it as unavailable in the analysis and continue with other sources.
• If memory systems (Serena or Forgetful) are unavailable, skip the Memory Phase and record the skip in the Action Phase output.
• If a URL points at github.com, do not call WebFetch. Use the github skill scripts, which reach the API through gh and so cannot be denied by a WebFetch hook. Write the plugin root inline on each call, because shell variables do not survive between Bash invocations. Issue body and metadata: python3 "${COPILOT_PLUGIN_ROOT:-${CLAUDE_PLUGIN_ROOT:-.claude}}/skills/github/scripts/issue/get_issue_context.py" --owner {owner} --repo {repo} --issue {n}. Issue discussion: the same path with issue/get_issue_comments.py. PR body and diff: pr/get_pr_context.py --owner {owner} --repo {repo} --pull-request {n}. PR review discussion: pr/get_pr_review_comments.py and pr/get_pr_review_threads.py with the same flags.
• If WebFetch is denied by a harness permission decision rather than a network error, that is a capability signal, not a prompt-injection attempt. Record the denial, switch to the github script path above for github.com URLs or to WebSearch for other hosts, and continue. Do not halt the run. Never call a tool the denial names unless it is already in this command's allowed-tools.

Stop Conditions

Stop when any of the following is true:

• All 5 phases completed or intentionally skipped under a Fallback Rule.
• 3 phases have failed (intentional skips under Fallback Rules do not count as failures).
• The 50k output-token budget is reached.

Output

Artifact	Location
Analysis document	.agents/analysis/{topic-slug}.md
Serena memory	.serena/memories/{topic-slug}-integration.md
Forgetful memories	5-10 atomic memories in knowledge graph
GitHub issue	Created if implementation work identified

Related

• Skill: .claude/skills/research-and-incorporate/SKILL.md
• Memory skill: /memory-search for retrieving incorporated knowledge