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.
git clone --depth 1 https://github.com/d-o-hub/github-template-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/d-o-hub/github-template-ai-agents/swarm-web-research)<a href="https://agentmods.dev/commands/d-o-hub/github-template-ai-agents/swarm-web-research"><img src="https://agentmods.dev/badge/commands/d-o-hub/github-template-ai-agents/swarm-web-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 | $0.00016 | $0.00150 |
| Opus 5 | $0.00008 | $0.00075 |
| Sonnet 5 | $0.00003 | $0.00030 |
| Haiku 4.5 | $0.00002 | $0.00015 |
Grade A, and why
swarm-web-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 4d 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.
What it actually says
Execute multi-agent swarm analysis using git worktrees with optimized web research.
Topic: $ARGUMENTS
Steps:
- Load skills:
do-web-doc-resolver,agent-coordination,git-github-workflow - Create git worktree for isolated analysis
- Execute web research using the resolver skill with optimized cascade
- Launch 3-agent swarm in parallel using task tool
- Synthesize findings into consolidated report
- Create PR with all analysis files
- Monitor GitHub Actions until checks pass
Save findings to analysis/SWARM_SYNTHESIS.md.
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.
- 4d ago First seen · 20 lines · 16 tokens per session scan A 1de1bb2a860c
swarm-web-research is a command published in the GitHub repository d-o-hub/github-template-ai-agents (2 stars, last pushed yesterday), licensed MIT. It adds 16 tokens to every session and 150 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 2026-09-03.
Other commands, from other repositories
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fest-show
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superpowers-execute
Execute the current GSD phase plan with Superpowers instead of gsd-execute-phase.
verify-math
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synthesise-reviews
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triage
Triage ServiceNow incidents — list open incidents, assess priority, investigate a specific INC, or analyze trends.