claim-verify
Use when the user has a results draft or a set of data-backed claims and wants each one adversarially verified against the underlying dataset before publishing — a pre-publication red-team of the findings. Extracts the discrete checkable claims from the draft, reproduces each claim's number against the data, stress-tests it against the threats most likely to kill it (outliers, confounds, Simpson's reversals, tiny subgroups, alternative specifications), and marks it verified, fragile, or refuted; fragile and refuted claims are revised — hedged, scoped, or retracted — until every claim is verifi
npx skills add gaasher/Agent-Loop-Skills --skill claim-verify --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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 anomal
- When to use
- Setup
- The loop
- Ledger
- Constraints
- Stops
What does the claim-verify skill do?
Use when the user has a results draft or a set of data-backed claims and wants each one adversarially verified against the underlying dataset before publishing — a pre-publication red-team of the findings. Extracts the discrete checkable claims from the draft, reproduces each claim's number against the data, stress-tests it against the threats most likely to kill it (outliers, confounds, Simpson's reversals, tiny subgroups, alternative specifications), and marks it verified, fragile, or refuted; fragile and refuted claims are revised — hedged, scoped, or retracted — until every claim is verifi
How do I install it?
Run `npx skills add gaasher/Agent-Loop-Skills --skill claim-verify --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From gaasher/Agent-Loop-Skills, a repository with 146 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.