
Claim-Grounding Auditor — Catch Unsupported Claims in AI Output
Audits any AI draft for unsupported claims — flags each one, grades its source, and returns a substantiation report.
- Gate RAG output before it reaches a user
- Audit research briefs for unsupported claims
- Final quality gate in multi-agent writing pipelines
$12
· or 60 creditsSecure checkout via Stripe
Included in download
- Gate RAG output before it reaches a user
- Audit research briefs for unsupported claims
- file_read automation included
- Ready for Codex CLI
See it in action
A real example of what this skill takes in and produces.
Sample input
Audit this draft against the provided source file. DRAFT (q3-market-brief.md): "Our API enforces a rate limit of 100 requests per minute, which makes it unsuitable for high-frequency trading. Competitor X has 2M users, and most teams migrate to us within 30 days." SOURCE (docs/api-reference.md): "Line 44: The public API is rate-limited to 100 requests/minute per key."
Sample output
SUBSTANTIATION REPORT Draft: q3-market-brief.md | Sources provided: 1 | Claims checked: 4 [GROUNDED] "The API rate limit is 100 requests/minute." Source: docs/api-reference.md L44 (primary, current) [INFERRED] "This makes the API unsuitable for high-frequency trading." Basis: combines the rate limit (L44) with an unstated throughput assumption. No source states this conclusion. -> Confirm or qualify. [WEAK] "Competitor X has 2M users." No source provided; figure is unverifiable as written. -> Add a current third-party source. [UNSUPPORTED] "Most teams migrate within 30 days." No supporting source found in provided material. -> Remove, or supply a source. SUMMARY: 1 Grounded, 1 Inferred, 1 Weak, 1 Unsupported ACTION REQUIRED: 1 unsupported claim and 2 unverifiable claims before publish.

Claim-Grounding Auditor — Catch Unsupported Claims in AI Output
Audits any AI draft for unsupported claims — flags each one, grades its source, and returns a substantiation report.
$12
· or 60 creditsSecure checkout via Stripe
Included in download
- Gate RAG output before it reaches a user
- Audit research briefs for unsupported claims
- file_read automation included
- Ready for Codex CLI
- Instant install
See it in action
A real example of what this skill takes in and produces.
Sample input
Audit this draft against the provided source file. DRAFT (q3-market-brief.md): "Our API enforces a rate limit of 100 requests per minute, which makes it unsuitable for high-frequency trading. Competitor X has 2M users, and most teams migrate to us within 30 days." SOURCE (docs/api-reference.md): "Line 44: The public API is rate-limited to 100 requests/minute per key."
Sample output
SUBSTANTIATION REPORT Draft: q3-market-brief.md | Sources provided: 1 | Claims checked: 4 [GROUNDED] "The API rate limit is 100 requests/minute." Source: docs/api-reference.md L44 (primary, current) [INFERRED] "This makes the API unsuitable for high-frequency trading." Basis: combines the rate limit (L44) with an unstated throughput assumption. No source states this conclusion. -> Confirm or qualify. [WEAK] "Competitor X has 2M users." No source provided; figure is unverifiable as written. -> Add a current third-party source. [UNSUPPORTED] "Most teams migrate within 30 days." No supporting source found in provided material. -> Remove, or supply a source. SUMMARY: 1 Grounded, 1 Inferred, 1 Weak, 1 Unsupported ACTION REQUIRED: 1 unsupported claim and 2 unverifiable claims before publish.
About This Skill
## What it does Claim-Grounding Auditor makes your agent treat every factual claim in a draft as a liability until it is grounded in a verifiable source. Given a draft — and the source material it was built from — the agent extracts every checkable claim, locates the supporting evidence, grades the strength of that source, and returns a structured substantiation report. It is domain-agnostic. It works on research reports, product copy, technical docs, RAG output, briefs, and summaries — any text where a confident-but-wrong sentence is a real cost. ## The classification framework Every claim is assigned exactly one status: - GROUNDED — directly supported by a strong, specific, citable source. - INFERRED — a reasonable conclusion assembled across sources or partly reasoned rather than stated. Flagged so a human can confirm the leap. - WEAK — supported only by a low-quality, outdated, circular, or non-authoritative source. Usable, at the author's risk. - UNSUPPORTED — no source found, or the source contradicts the claim. Must be fixed or removed. ## Source-strength hierarchy The agent ranks sources rather than treating all citations as equal: primary/authoritative/current first, then reputable secondary, then aggregated/tertiary, then weak signals (undated, self-referential, or marketing content). A claim supported only by weak sources cannot be graded higher than WEAK — no matter how confident the prose sounds. ## Fact vs. inference A core rule: the agent distinguishes what a source SAYS from what the draft CONCLUDES. If a sentence combines two facts into a new claim, that new claim is INFERRED, not GROUNDED — even when both inputs are solid. This is the most common way confident drafts smuggle in unverified conclusions, and the audit surfaces it explicitly. ## Sample output SUBSTANTIATION REPORT Draft: q3-market-brief.md | Sources: 4 | Claims checked: 12 [GROUNDED] "The API rate limit is 100 requests/minute." Source: docs/api-reference.md L44 (primary, current) [INFERRED] "This makes the API unsuitable for high-frequency trading." Basis: combines the rate limit with an unstated throughput assumption. No source states this. -> Confirm or qualify. [WEAK] "Competitor X has 2M users." Source: competitor's 2021 press release (outdated). -> Replace. [UNSUPPORTED] "Most teams migrate within 30 days." No supporting source found. -> Remove or supply a source. SUMMARY: 6 Grounded · 3 Inferred · 2 Weak · 1 Unsupported ## Why use this skill Standard prompting produces fluent text whose confidence is uncorrelated with its accuracy — the failure mode behind most "the agent made it up" incidents. This skill replaces tone-based trust with an explicit, auditable paper trail. It is built for anyone whose agent ships output other people act on: research and analyst agents, documentation pipelines, RAG systems, and content workflows where a single fabricated number is a real cost. The grading framework is ported from regulated scientific and technical publishing, where every claim must survive expert review with a traceable, graded source — a discipline that rarely exists in general-purpose AI tooling. ## Use cases - Gate RAG output before it reaches a user — flag anything not actually grounded in the retrieved documents. - Audit research briefs and analyst reports for unsupported or inferred claims. - Pre-flight marketing and product copy for statements that legal or comms would challenge. - Check technical documentation against the actual codebase or spec. - Run as a final quality gate in any multi-agent writing pipeline. ## Known limitations - The audit is only as good as the sources provided. With no source material, the agent flags internally unsupported or self-contradicting claims but cannot verify external facts. - It checks grounding and source strength, not domain correctness — a well-sourced claim from a flawed source passes as GROUNDED against that source. - It reads files within its declared scope and does not fetch the open web unless your agent separately provides that capability.
Use Cases
- Gate RAG output before it reaches a user
- Audit research briefs for unsupported claims
- Final quality gate in multi-agent writing pipelines
Known Limitations
The audit is only as strong as the sources you provide. With no source material, the skill can still flag internally unsupported or self-contradicting claims, but it cannot verify external facts. It checks grounding and source strength, not domain correctness, so a well-sourced claim drawn from a flawed source will pass as Grounded against that source. It reads files within its declared scope and does not fetch the open web unless your agent separately provides that capability.
How to Install
mkdir -p ~/.claude/skills && curl -sL https://www.agensi.io/api/install/claim-grounding-auditor-catch-unsupported-claims-in-ai-output -o /tmp/claim-grounding-auditor-catch-unsupported-claims-in-ai-output.zip && unzip -o /tmp/claim-grounding-auditor-catch-unsupported-claims-in-ai-output.zip -d ~/.claude/skills && rm /tmp/claim-grounding-auditor-catch-unsupported-claims-in-ai-output.zipFree skills install directly. Paid skills require purchase - use the download button above after buying.
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Permissions
File Scopes
Read-only. The skill reads the draft and any provided source files to verify claims against them. It does not write, execute, or access the network.
Works with any SKILL.md-compatible agent (Claude Code, Codex CLI, Cursor, VS Code Copilot, Gemini CLI). No runtime dependencies. Strongest when source material is provided alongside the draft.