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 vstorm-co/content-skills --skill content-auditgit clone --depth 1 https://github.com/vstorm-co/content-skillsWrote 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/vstorm-co/content-skills/content-audit)<a href="https://agentmods.dev/skills/vstorm-co/content-skills/content-audit"><img src="https://agentmods.dev/badge/skills/vstorm-co/content-skills/content-audit/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/vstorm-co/content-skills/content-audit"><img src="https://agentmods.dev/badge/skills/vstorm-co/content-skills/content-audit.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 | $0.00050 | $0.02400 |
| Opus 5 | $0.00025 | $0.01200 |
| Sonnet 5 | $0.00010 | $0.00480 |
| Haiku 4.5 | $0.00005 | $0.00240 |
Grade A, and why
content-audit 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 262 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Quality Audit
Overview
This skill audits content across three dimensions, each scored out of 100:
- Content Quality -- Anti-slop score, readability, hook strength, structural variety
- Brand Voice Consistency -- How well the content matches the voice profile in
brand/VOICE.md - Brand Visual Consistency -- For visual content (presentations, videos, infographics), how well it matches
brand/VISUAL.md
The composite score combines all applicable dimensions. For text-only content, the composite is based on dimensions 1 and 2. For visual content, all three dimensions contribute.
Modes
Quick Score (/content score)
Runs a fast assessment and returns:
- Composite score (out of 100)
- Top 3 issues to fix
- One-sentence summary
Use this for a quick pulse check on a draft.
Full Audit (/content audit)
Runs a comprehensive review and returns:
- Detailed scores for each dimension with subscores
- Line-level feedback with specific callouts
- Forbidden phrase detection
- Readability metrics
- Concrete fix suggestions for every issue found
- Before/after examples for the most critical issues
Use this before publishing.
Before You Start
-
Load brand references: Read
brand/VOICE.mdandbrand/VISUAL.mdif they exist. These define the scoring criteria for brand consistency. If they do not exist, score brand consistency against reasonable defaults and note that brand files should be created for more accurate scoring. -
Identify the content type: Blog post, thread, LinkedIn post, newsletter, video script, slide deck, etc. Different content types have different quality expectations.
-
Get the content: The user should provide the draft text or a path to the file containing the content.
Audit Flow
Stage 1: Content Quality Audit
Run the content through these checks. Reference slop-detector.md for the full pattern list and scoring.md for the scoring rubric.
Anti-Slop Detection
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 262 lines · 50 tokens per session scan A 13832fa98109
content-audit is a skill published in the GitHub repository vstorm-co/content-skills (22 stars, last pushed 4mo ago), licensed MIT. It adds 50 tokens to every session and 2,400 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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