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 skills/etr/groundwork/swarm-debugnpx skills add etr/groundwork --skill swarm-debuggit clone --depth 1 https://github.com/etr/groundworkWhat 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 | $0.00024 | $0.02933 |
| Opus 5 | $0.00012 | $0.01466 |
| Sonnet 5 | $0.00005 | $0.00587 |
| Haiku 4.5 | $0.00002 | $0.00293 |
Grade A, and why
swarm-debug 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 2d 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 — 321 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Swarm Debugging
Overview
Parallel adversarial investigation. Multiple teammates test competing hypotheses simultaneously, actively trying to disprove each other. Converges on root cause faster by fighting anchoring bias.
Core principle: One investigator anchors on their first theory. A team of investigators who must disprove each other cannot.
This skill extends the groundwork:debug workflow. Phases 1-2 and 4-5 follow that skill exactly. Phase 3 (ISOLATE) is replaced by parallel swarm investigation using Claude Code agent teams.
Pre-flight: Model Recommendation
Your current effort level is {{effort_level}}.
Skip this step silently if effort is high, xhigh, or max (the scale is low < medium < high < xhigh < max, so xhigh and max are already above high) AND you are Opus (1M context).
If effort is low or medium (i.e. below high), you MUST show the recommendation prompt — regardless of model.
If you are not Opus (1M context), you MUST show the recommendation prompt - regardless of effort level.
Otherwise → use AskUserQuestion:
{
"questions": [{
"question": "Do you want to switch? Hypothesis generation quality determines whether the entire swarm investigates the right space.\n\nTo switch: cancel, run `/model opus[1m]` and `/effort high`, then re-invoke this skill.",
"header": "Recommended: Opus (1M context) at high effort",
"options": [
{ "label": "Continue" },
{ "label": "Cancel — I'll switch first" }
],
"multiSelect": false
}]
}
If the user selects "Cancel — I'll switch first": output the switching commands above and stop. Do not proceed with the skill.
Prerequisites
This skill requires the agent teams experimental feature.
To enable:
- Set the environment variable:
CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=true - Or add to your Claude Code settings:
"experimentalAgentTeams": true
If agent teams is not available: Fall back to the standard groundwork:debug skill and run Phase 3 sequentially. Note to the user that enabling agent teams would allow parallel investigation.
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.
- 2d ago First seen · 321 lines · 24 tokens per session scan A fcfa088f2b94
swarm-debug is a skill published in the GitHub repository etr/groundwork (42 stars, last pushed 20d ago), licensed MIT. It adds 24 tokens to every session and 2,933 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.
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