Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/rjmurillo/ai-agents/researchgit clone --depth 1 https://github.com/rjmurillo/ai-agentsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/rjmurillo/ai-agents/research)<a href="https://agentmods.dev/commands/rjmurillo/ai-agents/research"><img src="https://agentmods.dev/badge/commands/rjmurillo/ai-agents/research.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00015 | $0.01014 |
| Opus 5 | $0.00008 | $0.00507 |
| Sonnet 5 | $0.00003 | $0.00203 |
| Haiku 4.5 | $0.00002 | $0.00101 |
Grade A, and why
research scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
- Research Phase: Check existing knowledge, fetch URLs, perform web searches
- Analysis Phase: Write 3000-5000 word analysis to
.agents/analysis/ - Applicability Phase: Map integration points with ai-agents project
- Memory Phase: Create Serena memory + 5-10 atomic Forgetful memories
- Action Phase: Create GitHub issue if implementation work identified, via
python3 "${COPILOT_PLUGIN_ROOT:-${CLAUDE_PLUGIN_ROOT:-.claude}}/skills/github/scripts/issue/new_issue.py"
Budget
Complete within 50k output tokens. If approaching the limit, summarize findings so far, persist partial analysis, and stop. Prefer completing fewer phases well over partial work across all phases.
Fallback Rules
- If
WebSearchreturns no results for a query, try 2 alternative phrasings, then proceed with available information. - If a
WebFetchURL is unreachable or returns a non-success status, note it as unavailable in the analysis and continue with other sources. - If memory systems (Serena or Forgetful) are unavailable, skip the Memory Phase and record the skip in the Action Phase output.
- If a URL points at github.com, do not call
WebFetch. Use the github skill scripts, which reach the API throughghand so cannot be denied by a WebFetch hook. Write the plugin root inline on each call, because shell variables do not survive between Bash invocations. Issue body and metadata:python3 "${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 withissue/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.pyandpr/get_pr_review_threads.pywith the same flags. - If
WebFetchis 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 toWebSearchfor other hosts, and continue. Do not halt the run. Never call a tool the denial names unless it is already in this command'sallowed-tools.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 86 lines · 15 tokens per session scan A a08ee89a1f75
research is a command published in the GitHub repository rjmurillo/ai-agents (45 stars, last pushed today), licensed MIT. It adds 15 tokens to every session and 1,014 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
notebook
Low-ceremony capture for ideas (half-formed, want to mature into stories), todos (concrete actions), and notes (durable project/team facts for future recall). One-line capture, conditional elaboration AUQ. Use BEFORE thoughts get forced into stories.
load-session
Load a synced session summary for context.
ingest
Ingest source material into an active wiki. Accepts URLs, file paths, PDFs, freeform text, or processes the inbox. Supports tweets via Grok MCP.
wiki-ingest
Ingest a source document into the LLM Wiki.
compass-verify
Verify the Merkle hash chain over /.claude/projects/ /memory/ and report any tampered or missing files.
brain-init
Interactively scaffold a personalized WORKSPACEBRAIN.md from a fresh template.