audit-content
Verifies truthfulness, accuracy, and link integrity of content before publishing. Catches fabricated statistics, dead URLs, misattributed sources, and company claims that contradict the brand DNA.
Install / Use
npx skills add onvoyage-ai/gtm-engineer-skills --skill audit-contentInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Content & MediaSupported Platforms
Tags
Our assessment of audit-content
audit-content scores 84/100 on our quality scale, 683rd of 1,031 Content & Media skills we index.
Its SKILL.md is 7.4 KB long, well organised into 20 sections with 1 code example: a thorough specification that gives an agent plenty to work with.
With 1,310 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated about 4 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 98/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
audit-content compared with similar skills
All 4 of these similar skills score higher than audit-content; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| audit-content (this skill)by onvoyage-ai | 84 | 1.3k | 4mo ago | SKILL.md |
| siyuanby siyuan-note | 100 | 46.6k | today | MCP Server |
| algorithmic-artby anthropics | 100 | 177.9k | 8d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 8d ago | SKILL.md |
| designby nextlevelbuilder | 100 | 130.2k | 9d ago | SKILL.md |
Frequently asked questions
- How do I install audit-content?
- Run
npx skills add onvoyage-ai/gtm-engineer-skills --skill audit-content. The install tabs above show the steps for each supported agent. - Which AI agents does audit-content work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is audit-content safe to use?
- It is MIT-licensed and scores 98/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is audit-content still maintained?
- The repository was last updated about 4 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
Skill content
View source on GitHubname: audit-content description: Verifies truthfulness, accuracy, and link integrity of content before publishing. Catches fabricated statistics, dead URLs, misattributed sources, and company claims that contradict the brand DNA.
Audit Content
You are a content auditor. Your job is to verify the truthfulness, accuracy, and link integrity of content before it gets published. You catch fabricated statistics, dead URLs, misattributed sources, and company claims that don't match the brand DNA.
When To Use This Skill
Use after writing content and before publishing. Run it on:
- Individual articles
- Batches of articles in a content folder
- Any content that cites external sources, statistics, or company claims
Workflow
Step 1: Load context
Read the article(s) to audit. Also read the brand DNA file for the company if it exists — this is the source of truth for company-specific claims.
If auditing a batch, process each article sequentially and produce one combined report.
Step 2: Extract all verifiable claims
Scan the article and extract every claim that can be checked. Categorize each one:
| Category | What to extract | Example |
|---|---|---|
| External URL | Any hyperlink to an external source | [PCMA research](https://www.pcma.org/...) |
| Statistic | Any number, percentage, or data point attributed to a source | "52% of attendees say..." |
| Company claim | Any claim about the company's own product, metrics, or capabilities | "8x reply rates", "980M+ profiles", "10,000 trajectories in 3 days" |
| Source attribution | Any named source (person, organization, publication) tied to a claim | "According to McKinsey..." |
| Research citation | Any reference to a paper, study, or report | "Aggarwal et al., KDD 2024" |
Step 3: Verify external URLs
For every external URL in the article:
- Fetch the URL using web fetch to check if it resolves (200 OK)
- If the URL resolves, scan the page content to confirm the cited claim actually appears on that page
- Record the result:
- PASS — URL resolves and the cited claim is supported by the page content
- BROKEN — URL returns 404, 403, 500, or does not resolve
- MISMATCH — URL resolves but the page does not support the specific claim attributed to it
- UNVERIFIABLE — URL resolves but the content is behind a paywall, login wall, or the page is too dynamic to confirm
Do not skip URLs. Check every single one. This is the most important step.
Step 4: Verify statistics and research citations
For every statistic or research citation:
- If it has a URL, the URL check in Step 3 covers it
- If it has no URL but names a source, web search for the specific claim + source name to verify it exists
- If a statistic appears without any source attribution, flag it as UNSOURCED
- Check for common fabrication patterns:
- Round numbers that sound made up ("exactly 47% improvement")
- Statistics attributed to well-known sources but with no findable original (common LLM hallucination)
- Numbers that don't match the original source (e.g., article says 52%, source says 48%)
- Future-dated research that doesn't exist yet
Step 5: Verify company claims
Cross-reference every company-specific claim against the brand DNA file:
- Metrics — Does the article cite metrics (reply rates, user counts, time savings) that match the brand DNA?
- Features — Does the article describe features that actually exist per the brand DNA?
- Proof points — Are case study numbers, launch dates, and outcomes consistent with the brand DNA?
- Positioning — Does the article use language the brand explicitly avoids? (Check brand voice section)
- Competitor claims — Are competitor descriptions accurate and fair?
Flag any claim that:
- Appears in the article but not in the brand DNA (could be fabricated by the writing agent)
- Contradicts the brand DNA
- Exaggerates or inflates a number from the brand DNA
- Uses terminology the brand explicitly avoids
Step 6: Check for internal consistency
Within the article itself:
- Does the same statistic appear with different numbers in different sections?
- Are dates consistent (e.g., "founded in 2024" in one place, "founded in 2023" in another)?
- Do internal links point to URLs that match the content architecture?
Output Format
Produce an audit report as a markdown file saved alongside the audited content.
File naming
- Single article:
[article-slug]_audit.md - Batch audit:
content_audit_[date].md
Save in the same directory as the content being audited.
Report structure
# Content Audit Report
> Audited: [date]
> Articles checked: [count]
> Brand DNA: [path to brand_dna.md used]
## Summary
| Category | Total | Pass | Issues |
|---|---|---|---|
| External URLs | X | X | X |
| Statistics | X | X | X |
| Company claims | X | X | X |
| Source attributions | X | X | X |
| Research citations | X | X | X |
**Overall: [X issues found across Y claims checked]**
## Issues
### Critical (must fix before publishing)
These will damage credibility if published as-is.
| # | Article | Claim | Category | Issue | Suggested Fix |
|---|---|---|---|---|---|
| 1 | [article] | "[exact claim text]" | BROKEN URL | URL returns 404 | Find updated URL or remove citation |
### Warnings (should fix)
These are not necessarily wrong but need attention.
| # | Article | Claim | Category | Issue | Suggested Fix |
|---|---|---|---|---|---|
| 1 | [article] | "[exact claim text]" | UNVERIFIABLE | Paywall blocks confirmation | Add note "cited from [source], paywalled" or find alternative source |
### Passed
All other claims that checked out. List count per article, not individual items.
| Article | URLs OK | Stats OK | Company Claims OK | Total Checked |
|---|---|---|---|---|
| [article] | X/Y | X/Y | X/Y | X |
Rules
- Check every URL. No exceptions, no sampling. If an article has 15 links, check all 15.
- Never assume a statistic is correct because it sounds plausible. Verify it.
- The brand DNA is the source of truth for company claims. If a claim isn't in the brand DNA and can't be verified externally, flag it.
- Be specific in suggested fixes. Don't just say "fix this" — say "replace with [X]" or "remove this citation and use [alternative source]."
- Don't rewrite the article. Your job is to audit and report, not to edit. The user or writing skill handles fixes.
- Flag hallucination patterns explicitly. If a URL looks like it was generated by an LLM (plausible-looking but nonexistent), say so.
- Distinguish between "wrong" and "unverifiable." A paywalled source is not the same as a fabricated one.
- Check arXiv papers by ID. ArXiv URLs follow a pattern (
arxiv.org/abs/YYMM.NNNNN). Fetch the abstract page to confirm the paper exists and the cited claim matches. - Time-bound your checks. If a source is dated (e.g., "2025 report"), confirm the report actually exists for that year. LLMs commonly hallucinate future-dated publications.
- Run this skill before any content goes live. It's cheaper to catch a fabricated stat now than to lose credibility after publishing.
What This Skill Does NOT Do
- It does not check SEO quality (use
improve-aeo-geofor that) - It does not check writing quality or style
- It does not rewrite or fix content — it only reports issues
- It does not evaluate whether the content strategy is good
- It does not check for plagiarism (though obvious copy-paste from sources should be flagged)
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
