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/madappgang/magus/researchgit clone --depth 1 https://github.com/MadAppGang/magusWrote 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/madappgang/magus/research)<a href="https://agentmods.dev/commands/madappgang/magus/research"><img src="https://agentmods.dev/badge/commands/madappgang/magus/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 | $0.00013 | $0.07239 |
| Opus 5 | $0.00006 | $0.03619 |
| Sonnet 5 | $0.00003 | $0.01448 |
| Haiku 4.5 | $0.00001 | $0.00724 |
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 yesterday.
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.
This is a copy
89% identical to deep-research — 129 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 899 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Apply answer convergence criteria to determine when research is complete,
avoiding both premature stopping and wasteful over-exploration.
<user_request> $ARGUMENTS </user_request>
<critical_override> THIS COMMAND OVERRIDES THE CLAUDE.md TASK ROUTING TABLE FOR AGENT SELECTION.
WHY: The CLAUDE.md routing table may map "research" tasks to dev:developer when "implement" keywords appear in the research topic. ALL web exploration in this command MUST go to dev:researcher agents, not dev:developer.
AGENT RULES FOR THIS COMMAND:
- Research planning → dev:developer agent (used as planner, NOT for web research)
- Query generation → dev:developer agent (used as planner)
- Web exploration → dev:researcher agents (parallel, up to 3)
- Local investigation → dev:researcher agents
- Finding synthesis → dev:synthesizer agent (subagent_type: "dev:synthesizer")
- Report generation → dev:synthesizer agent
DO NOT use dev:developer for web exploration (dev:developer writes code, not research). DO NOT use dev:architect for research (dev:architect plans systems, not research). DO NOT use code-analysis:detective (READ-ONLY codebase analysis, not web research). </critical_override>
Before starting, create comprehensive todo list:
1. PHASE 0: Session initialization
2. PHASE 1: Research planning (decompose topic)
3. PHASE 2: Question development (generate search queries)
4. PHASE 3: Web exploration (parallel agent execution)
5. PHASE 4: Report synthesis (consolidate findings)
6. PHASE 5: Convergence check (iterate if needed)
7. PHASE 6: Finalization (present report)
Update continuously as you progress.
Mark only ONE task as in_progress at a time.
</todowrite_requirement>
<orchestrator_role>
**You are an ORCHESTRATOR, not RESEARCHER.**
**You MUST:**
- Use Agent tool to delegate ALL research to agents
- Use Tasks to track research pipeline
- Enforce convergence criteria between iterations
- Use file-based communication between agents
- Track iteration count and apply finalization criteria
**You MUST NOT:**
- Write research findings yourself
- Skip convergence checks
- Exceed iteration limits without user approval
- Pass large content through Task prompts
</orchestrator_role>
<file_based_communication>
**All agent communication happens through files:**
- Planner writes to ${SESSION_PATH}/research-plan.md
- Each Explorer writes to ${SESSION_PATH}/findings/explorer-{N}.md
- Synthesizer writes to ${SESSION_PATH}/synthesis/iteration-{N}.md
- Final report at ${SESSION_PATH}/report.md
**Why:**
- Prevents context pollution
- Enables parallel execution
- Creates audit trail for research provenance
- Allows resume from any phase
</file_based_communication>
<delegation_rules>
- Research planning: developer agent (used as planner)
- Query generation: developer agent (used as planner)
- Web exploration: researcher agents (parallel, up to 3)
- Local investigation: researcher agents
- Finding synthesis: synthesizer agent
- Report generation: synthesizer agent
</delegation_rules>
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.
- yesterday First seen · 899 lines · 13 tokens per session scan A 139001071802
research is a command published in the GitHub repository MadAppGang/magus (9 stars, last pushed yesterday), licensed MIT. It adds 13 tokens to every session and 7,239 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to deep-research, differing in 129 lines, and is treated as a copy.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
constitution
Create or update the project constitution from interactive or provided principle inputs.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.