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/verify/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/verify)<a href="https://agentmods.dev/skills/swarm-ai-research/swarm/verify"><img src="https://agentmods.dev/badge/skills/swarm-ai-research/swarm/verify/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/verify"><img src="https://agentmods.dev/badge/skills/swarm-ai-research/swarm/verify.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, 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.
- medium Excessive Agency · line 22 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00050 | $0.00829 |
| Opus 5 | $0.00025 | $0.00415 |
| Sonnet 5 | $0.00010 | $0.00166 |
| Haiku 4.5 | $0.00005 | $0.00083 |
Grade A, and why
verify 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 — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
EXECUTE NOW
Target: $ARGUMENTS
Parse immediately:
--claims→ only check claim cards (Step 2)--quick→ schema validation only, skip wiki-links and health (Steps 1–2)--fullor empty → run everything (Steps 1–6)
Execute all applicable steps without asking for confirmation.
Step 1: Validate Run Schemas
Run the validation script:
python scripts/validate-run.py --all
Report:
- Total runs validated
- Number of errors
- List any errors with run_id and field
Step 2: Validate Vault Notes
Run the vault validation script:
python scripts/validate-vault.py --all
This checks:
- Claim cards: schema compliance, description length, confidence validity, evidence provenance, topics footer
- Experiment notes: required fields, description constraints, run references, topics footer
- Index consistency: claims referenced in _index.md, experiments directory referenced
Report each category separately.
Step 3: Vault Health Audit
Run the comprehensive health audit:
python scripts/vault-health.py
This checks:
- Claim status distribution (active, weakened, superseded, retracted)
- Confidence distribution (high, medium, low, contested)
- Stale claims (not updated in >30 days)
- Broken run references in evidence
- Broken wiki-links (excluding templates)
- Orphaned notes not in index
Step 4: Check Run Index Freshness
cp run-index.yaml run-index.yaml.bak
python scripts/index-runs.py
diff run-index.yaml.bak run-index.yaml
rm run-index.yaml.bak
If the index changed, report that it was stale and has been rebuilt. If no changes, report the index is up to date.
Step 5: Check Unsynthesized Runs
python scripts/generate-note.py
(No arguments = lists unsynthesized runs)
Report how many runs lack experiment notes.
Step 6: Generate Dashboard
Compile all results into a single dashboard:
## Vault Verification Report
### Schema validation
- Runs: {N} validated, {E} errors
- Claims: {N} validated, {E} errors
- Experiments: {N} validated, {E} errors
### Health
- Claims: {total} total ({active} active, {weakened} weakened)
- Confidence: {high} high, {medium} medium, {low} low, {contested} contested
- Stale (>30d): {stale}
- Broken references: {broken_refs}
- Broken wiki-links: {broken_links}
### Index
- Run index: {status}
- Unsynthesized runs: {count}
### Overall
{PASS if 0 errors, WARN if only warnings, FAIL if errors}
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.
- 5d ago First seen · 137 lines · 50 tokens per session scan A 6693f247c09b
verify is a skill published in the GitHub repository swarm-ai-research/swarm (42 stars, last pushed today), licensed MIT. It adds 50 tokens to every session and 829 once invoked, about $0.0003 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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