Borrowing it
Nothing to install: this file belongs to swarm-ai-research/swarm. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/swarm-ai-research/swarm/main/.skills/claim/SKILL.mdgit clone --depth 1 https://github.com/swarm-ai-research/swarmWrote 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/skills/swarm-ai-research/swarm/claim)<a href="https://agentmods.dev/skills/swarm-ai-research/swarm/claim"><img src="https://agentmods.dev/badge/skills/swarm-ai-research/swarm/claim/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/swarm-ai-research/swarm/claim"><img src="https://agentmods.dev/badge/skills/swarm-ai-research/swarm/claim.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 9 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
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 | $0.00073 | $0.01977 |
| Opus 5 | $0.00036 | $0.00988 |
| Sonnet 5 | $0.00015 | $0.00395 |
| Haiku 4.5 | $0.00007 | $0.00198 |
Grade A, and why
claim 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 7d 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 — 218 lines — stays where its author put it; the contents beside it link to each section on GitHub.
EXECUTE NOW
Target: $ARGUMENTS
Parse immediately:
create [proposition]→ create a new claim card (Step 1–6)update [claim-id]→ update an existing claim (Step 7–9)status→ show claim health dashboard (Step 10)list→ list all claims with status and confidence (Step 11)- Empty → show help with subcommand options
CREATE MODE: Steps 1–6
Step 1: Parse Proposition
The proposition is the claim stated as a testable sentence. It becomes both the filename and the H1 title.
Rules:
- Must be a complete proposition (not a label or question)
- Composability test: "This note argues that [proposition]"
- Lowercase, no trailing period
- Filename: kebab-case with
claim-prefix. E.g., "circuit breakers alone outperform full governance stacks" →claim-circuit-breakers-alone-outperform-full-governance-stacks.md - Truncate filename to max 80 chars if needed
If no proposition provided, ask: "State the claim as a testable proposition (e.g., 'transaction tax above 5% reduces welfare')."
Step 2: Gather Evidence
Search for supporting runs:
- Ask the user: "Which run(s) support this claim? (run_id or 'search')"
- If user says "search":
- Ask for keywords related to the claim
- Search
run-index.yamlby tags - Search
runs/*/summary.jsonfor relevant metrics - Present top candidates with one-line summaries
- For each supporting run, extract:
run_id- Primary metric and value
- Effect size (Cohen's d), p-value, correction method, sample size
- Construct the
detailstring:"d={d}, p={p}, N={N}, {correction}-corrected"
Step 3: Assess Confidence
Based on the evidence gathered, recommend a confidence level:
| Confidence | Criteria |
|---|---|
| high | Bonferroni-significant AND replicated across ≥2 independent runs/seeds |
| medium | Nominally significant OR single-sweep support with BH correction |
| low | Suggestive but underpowered (<20 seeds) or unreplicated |
| contested | Conflicting evidence from different runs |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 7d ago First seen · 218 lines · 73 tokens per session scan A 9dcf1629d386
claim is a skill published in the GitHub repository swarm-ai-research/swarm (42 stars, last pushed today), licensed MIT. It adds 73 tokens to every session and 1,977 once invoked, about $0.0004 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.
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