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/gaasher/agent-loop-skills/claim-verifynpx skills add gaasher/Agent-Loop-Skills --skill claim-verifygit clone --depth 1 https://github.com/gaasher/Agent-Loop-SkillsWrote 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/gaasher/agent-loop-skills/claim-verify)<a href="https://agentmods.dev/skills/gaasher/agent-loop-skills/claim-verify"><img src="https://agentmods.dev/badge/skills/gaasher/agent-loop-skills/claim-verify.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 | $0.00190 | $0.02225 |
| Opus 5 | $0.00095 | $0.01112 |
| Sonnet 5 | $0.00038 | $0.00445 |
| Haiku 4.5 | $0.00019 | $0.00222 |
Grade A, and why
claim-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 — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Claim Verify Loop
A claim-by-claim adversarial verification loop over a results draft. The artifact is the draft; the feedback signal is the count of unverified claims — claims not yet checked, or checked but not yet survived a stress test. You drive it to zero: each claim ends verified (reproduces and survives the obvious threats) or appropriately qualified (hedged, scoped, or retracted with the reason).
The discipline: a number that merely reproduces is not trustworthy — most wrong findings reproduce fine. A claim is verified only when it also survives the threat most likely to kill it: an outlier, a confound, a subgroup too small to mean anything, a sign that flips under stratification. This loop is a gate on an existing draft, not a generator of new findings.
When to use
Use this when you have a draft (or a list of claims) drawn from a dataset and want each claim
red-teamed before it goes out. Default to verifying every discrete claim in the draft; if the user
flags a few high-stakes claims, prioritize those but still sweep the rest. Not for open-ended
discovery of new findings (that is the data-analysis loop) and not for diagnosing one known anomaly.
Setup
Resolve bindings interactively. If loop.run.yaml exists in the working dir, load it, confirm the
values in one line, and skip to the loop. Otherwise: on Claude Code (the AskUserQuestion tool is
available) infer a likely value for each binding and present it as the recommended option; on other
hosts ask each as a quoted plain-text prompt. Then write loop.run.yaml (format:
examples/run.example.yaml) and confirm the values before creating any other files.
| binding | meaning | default | how to infer |
|---|---|---|---|
<draft> |
results/claims document to verify (markdown/text) | — | scan the working dir for a results/report file |
<dataset> |
data the claims were drawn from; read-only ground truth | — | scan the working dir for the data file |
<analysis_cmd> |
interpreter that runs check snippets in the user's env | python3 |
pyproject.toml/.venv/uv in the working dir |
<report> |
the verified/revised draft this loop produces | <sandbox_root>/verified.md |
— |
<sandbox_root> |
where check snippets + ledger live | ./sandbox |
— |
<budget> |
max iterations | 10 | — |
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 · 144 lines · 190 tokens per session scan A fb51bed45551
claim-verify is a skill published in the GitHub repository gaasher/Agent-Loop-Skills (163 stars, last pushed 2mo ago), licensed MIT. It adds 190 tokens to every session and 2,225 once invoked, about $0.0010 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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