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Verify Claims

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pedrohcgs
verify-claims

Run Chain-of-Verification (CoVe) on a draft or a block of text with factual claims. Spawns the `claim-verifier` agent in a fresh context (never a conversation fork) so it never sees the draft — then reports which claims are supported, contradicted, or unverifiable. Use when user says "verify these citations", "check the claims in X", "did I hallucinate anything", "fact-check this draft", "run CoVe on this", or after any text generation that asserts facts about papers, datasets, or numerical results. NOT for style/grammar review (use `/proofread`) or substance review (use `/review-paper`).

Overview

Publisherpedrohcgs
Repositoryclaude-code-my-workflow
Skill nameverify-claims
Stars
1.6K
Forks
3.1K
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by pedrohcgs on GitHub. Read the source before you install it.

Installation

Install the Verify Claims AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/pedrohcgs/claude-code-my-workflow/tree/main/.claude/skills/verify-claims
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/pedrohcgs/claude-code-my-workflow.git /tmp/claude-code-my-workflow
mkdir -p .claude/skills
cp -r /tmp/claude-code-my-workflow/.claude/skills/verify-claims .claude/skills/verify-claims
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Verify Claims in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Verify Claims on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Verify Claims is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

/verify-claims — Chain-of-Verification on a Draft

Fact-check a draft using the Post-Flight Verification protocol (.claude/rules/post-flight-verification.md).

Input: $ARGUMENTS — path to a file containing the draft (markdown, .qmd, .tex, .md) or a shorthand pointer. Optional flags:

  • --source <path-or-url> — one or more source-material pointers (repeat for multiple). If omitted, the skill infers from context (e.g., papers referenced, cited arXiv URLs).
  • --no-fail-closed — downgrade FAIL outcomes to warnings without regeneration. Use sparingly.

When to pick this skill

  • /verify-claims (this skill) — ad-hoc fact-checking on any draft or text block the user hands you. One-shot, user-invoked.
  • Other skills that auto-run Post-Flight internally (/lit-review, /research-ideation, /respond-to-referees, /review-paper --peer) — no need to call this separately; they already run it.
  • /proofread — grammar, typos, overflow. Different lens.
  • /review-paper (default mode) — full manuscript review, not just claim verification.
  • /validate-bib — checks citations exist and are well-formed (structural + DOI). This skill checks they hold (the cited paper supports the attributed claim). Complementary — run both before submission.

How it works

Implements the 4-step CoVe loop from Dhuliawala et al. 2023 (arXiv:2309.11495), with architectural enforcement of the fresh-context independence trick.

Phase 0 — Pre-Flight

Confirm:

  • Draft file exists and is readable
  • At least one source pointer available (either --source or auto-detected from draft)
  • claim-verifier agent file exists at .claude/agents/claim-verifier.md

If any fail → surface the failure, do NOT proceed.

Phase 1 — Extract claims

Read the draft. Identify factual assertions of these types:

TypeExample
Citation"Smith (2019, JEL) shows X"
Numerical fact"N = 10,000", "ATT = 0.42"
Negative literature"No prior work studies X"
Named entityresearcher, paper title, venue, package, estimator name
Dataset claim"The CPS contains field educ_attain"

Skip: opinions, forward-looking suggestions, definitions the draft introduces.

For citation-type claims, extract the claim↔citation PAIR — not just the citation. Capture what the draft attributes to which work, so the verifier checks appropriateness (does Smith 2019 actually show X?), not merely existence. "Smith (2019) shows a positive wage effect" becomes {cite: Smith2019, attributed: "positive wage effect"}. This is the layer /validate-bib explicitly defers here: validate-bib confirms the citation exists and is well-formed; this skill confirms it holds. A mis-citation (the paper exists but says something else, or the opposite) is exactly a numeric/directional contradiction → HIGH-WARN unless a concrete author_alternative is recorded (then EXPLAINED).

Output a claims table:

markdown
| ID | Claim | Source hint |
|----|-------|-------------|
| C1 | ... | ... |

Phase 2 — Generate verification questions

One question per claim. Make it specific and answerable from the source alone.

Phase 3 — Spawn claim-verifier (fresh context — never a conversation fork)

Agent: subagent_type=claim-verifier   # a named subagent starts fresh; a /fork copy would inherit the draft
Prompt: hand over claims table + verification questions + source material pointers.
        Do NOT include the draft text.

The forked agent runs the CoVe independent-answer step. It has never seen the draft and cannot confirm-bias. It returns a structured verification report.

Phase 4 — Reconcile

The verifier returns a per-claim verdict in one of these severity tiers:

  • HIGH-WARN — fabricated reference (the cited paper doesn't exist at the named venue/year), draft claim directly contradicted by the source, or not_found retrieval that the verifier interprets as a hallucinated citation. Fail closed — surface these first and never present the draft as verified while one stands. This is a reporting rule, not a mechanical gate: nothing in /commit or the pre-commit hook reads these verdicts, so the author decides, and a HIGH-WARN left in place is stated in the report the user sees.
  • MED-WARN — transient infrastructure / retrieval failure (paywall the verifier can normally bypass via cached metadata; DOI resolver timeout; partial PDF read). Surface for the author; do not gate-refuse.
  • LOW-WARN — source genuinely inaccessible (paywalled and not in cache; private dataset; pre-print server transient). Surface with cannot-verify flag; do not gate-refuse.
  • EXPLAINED (v2.0) — a numeric/directional contradiction the author has pre-justified with a concrete named alternative (different defensible edition, specification, sample, or rounding convention), passed to the verifier via the claim's author_alternative field. Surfaced with the evidence and the recorded reason; non-gating. The hard floor holds: a fabricated citation is never EXPLAINED, and a blank/vague alternative stays HIGH-WARN. This mirrors audit-reproducibility's EXPLAINED disposition for numeric claims — a mismatch is not always a failure when a defensible alternative is named.

Verdict aggregation by tier across all extracted claims (EXPLAINED counts as non-gating, like LOW):

Tier countsOutcomeWhat the report says
0 HIGH, 0 MED, ≥ 0 LOW/EXPLAINEDPASS (green block)draft verified
0 HIGH, ≥ 1 MED, any LOW/EXPLAINEDPARTIAL (yellow block)verified with warnings
≥ 1 HIGHFAIL (red block)never reported as verified while a HIGH-WARN stands (unless --no-fail-closed)

--no-fail-closed reports HIGH-WARN verdicts as ordinary warnings instead of failing closed. Use sparingly — it's there for offline / hallucination-sensitive contexts where the user accepts the risk in writing.

If the draft is writeable and the user asked for auto-correction, regenerate the affected sections using the verifier's evidence. Otherwise return the report and let the user decide.

Example

/verify-claims quality_reports/lit-review_measurement-error.md --source master_supporting_docs/author_2021_method.pdf --source master_supporting_docs/coauthor_2020_survey.pdf

Expected output (abridged):

markdown
## Post-Flight Verification — lit-review_measurement-error.md

**Claims extracted:** 14
**Verified independently:** 14 (fresh-context claim-verifier)
**Outcome:** FAIL — 12 verified, 1 contradicted by its source (HIGH-WARN), 1 unverifiable (LOW-WARN); the draft is not reported as verified until C7 is corrected

### Discrepancies

- **C7** — draft claims "Coauthor (2020) *proposes* a bias-corrected estimator." Source Section 4 shows they propose a weighting estimator, not a bias-corrected one. Recommend correction.

### Unverifiable

- **C12** — draft cites "Third Author et al. 2024 (working paper)". No canonical URL in provided sources. Recommend user supply DOI or arXiv link.

### Verified

| ID | Claim | Evidence |
|----|-------|----------|
| C1 | "Author 2021 defines the calibration constant as a ratio of moments" | p. 5, eq. (3) |
| ... | ... | ... |

Fail modes and recovery

Verifier times out: surface a warning block, return draft as provisional. Do not silently ship.

Source material inaccessible (paywall, 404): report the specific claims that hinge on it, flag as cannot-verify, recommend user supply an alternative source.

Draft contains only opinions / forward-looking text: report "no verifiable factual claims extracted — nothing to check" and return.

Cross-references

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Verify Claims AI skill do?

Run Chain-of-Verification (CoVe) on a draft or a block of text with factual claims. Spawns the `claim-verifier` agent in a fresh context (never a conversation fork) so it never sees the draft — then reports which claims are supported, contradicted, or unverifiable. Use when user says "verify these citations", "check the claims in X", "did I hallucinate anything", "fact-check this draft", "run CoVe on this", or after any text generation that asserts facts about papers, datasets, or numerical results. NOT for style/grammar review (use `/proofread`) or substance review (use `/review-paper`).

Why use Verify Claims on TypingMind?

Because you install it once and use it with any model. Verify Claims is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Verify Claims in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/pedrohcgs/claude-code-my-workflow/tree/main/.claude/skills/verify-claims. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Verify Claims?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Verify Claims?

As many as you like. As long as a model supports skills, you can use Verify Claims with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Verify Claims AI skill free?

Yes. It is published on GitHub by pedrohcgs under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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