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 jason21wc/ai-governance-mcp --skill content-enhancergit clone --depth 1 https://github.com/jason21wc/ai-governance-mcpWrote 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/jason21wc/ai-governance-mcp/content-enhancer)<a href="https://agentmods.dev/skills/jason21wc/ai-governance-mcp/content-enhancer"><img src="https://agentmods.dev/badge/skills/jason21wc/ai-governance-mcp/content-enhancer/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/jason21wc/ai-governance-mcp/content-enhancer"><img src="https://agentmods.dev/badge/skills/jason21wc/ai-governance-mcp/content-enhancer.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 | $0.00061 | $0.03188 |
| Opus 5 | $0.00030 | $0.01594 |
| Sonnet 5 | $0.00012 | $0.00638 |
| Haiku 4.5 | $0.00006 | $0.00319 |
Grade A, and why
content-enhancer scanned grade A with 1 finding 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 11d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -sL -o "enhanced/{slug}/fig-{NN}-{descriptor}.{ext}" "https://example.com/image.png" How it starts
The opening of the file, as written. The whole thing — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Runtime Context
After the skill loads, establish the current date and source location with ordinary tool calls. Do not execute host-specific shell while the skill is loading.
Instructions
You are running the content enhancer skill. Read procedure.md in this skill folder for the full 5-step protocol.
Execution Protocol
-
Collect the Runtime Context above, then call
evaluate_governance(planned_action="content enhancement")before any writes. -
Get the source content. If the user has not already provided it, ask: "What content would you like me to enhance? You can paste text, provide a file path, or share a URL."
-
Extract visual content (if source is a file with embedded images). Skip this step for pasted text, transcripts, or text-only sources.
Format detection → strategy. Identify the source format and map it to an extraction strategy — the format determines the mechanism, not just the parser:
Source type Strategy Embedded raster (PDF, DOCX, HTML, Markdown) Extract embedded images (below) Native-rendered deck (PPTX with shapes/charts) Render slides if LibreOffice present, else escalate to user PDF export Legacy binary ( .doc,.ppt)Convert first to a modern format, then re-run detection Tabular (XLSX / spreadsheet) Tabularize → Markdown tables (not image extraction) Multi-file folder Orchestrate across files (below) Unknown / encrypted / corrupt Escalate (terminal branches, below) Web-sourced visuals are gap-filling, not extraction. If a visual gap needs a figure the provided source lacks, handle it via the Gap-Filling Protocol's visual lane (re-express data as a table, or link+describe) — never embed or synthesize a third-party image. This Step-3 path applies only to images already present in a provided source.
Output directory setup:
mkdir -p enhanced/{slug}{slug}= slugified document title or filename (lowercase, hyphens for spaces, no special characters). If the user provides a name, use it. The enhanced document will be written toenhanced/{slug}/index.md.
What ships with it
1 file 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.
- 11d ago First seen · 154 lines · 61 tokens per session scan A cba423e27f0a
content-enhancer is a skill published in the GitHub repository jason21wc/ai-governance-mcp (0 stars, last pushed 11d ago), licensed Apache-2.0. It adds 61 tokens to every session and 3,188 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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