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 skills add tonydzi/second-brain-starter-kit --skill audit-contentgit clone --depth 1 https://github.com/tonydzi/second-brain-starter-kitWrote 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/tonydzi/second-brain-starter-kit/audit-content)<a href="https://agentmods.dev/skills/tonydzi/second-brain-starter-kit/audit-content"><img src="https://agentmods.dev/badge/skills/tonydzi/second-brain-starter-kit/audit-content/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/tonydzi/second-brain-starter-kit/audit-content"><img src="https://agentmods.dev/badge/skills/tonydzi/second-brain-starter-kit/audit-content.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00040 | $0.02133 |
| Opus 5.5 | $0.00016 | $0.00853 |
| Sonnet 5.5 | $0.00008 | $0.00427 |
| Haiku 4.5 | $0.00004 | $0.00213 |
Grade A, and why
audit-content 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 6d 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.
This is a copy
100% identical to audit-content — 14 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
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.
- 6d ago Changed 54526a43006d
- 19d ago Changed · -1 lines ad197415c260
- 24d ago Changed · +13 lines 39ef2a695fa6
- 1mo ago First seen · 170 lines · 40 tokens per session scan A 2d3404532ae2
audit-content is a skill published in the GitHub repository tonydzi/second-brain-starter-kit (12 stars, last pushed yesterday), licensed MIT. It adds 40 tokens to every session and 2,133 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to audit-content, differing in 14 lines, and is treated as a copy.
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