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 agentmods add skills/frabcd/codex-ai-game-studio/content-auditnpx skills add frabcd/codex-ai-game-studio --skill content-auditgit clone --depth 1 https://github.com/frabcd/codex-ai-game-studioWrote 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/frabcd/codex-ai-game-studio/content-audit)<a href="https://agentmods.dev/skills/frabcd/codex-ai-game-studio/content-audit"><img src="https://agentmods.dev/badge/skills/frabcd/codex-ai-game-studio/content-audit.svg" alt="Measured on agentmods" 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 | $0.00022 | $0.01955 |
| Opus 5 | $0.00011 | $0.00978 |
| Sonnet 5 | $0.00004 | $0.00391 |
| Haiku 4.5 | $0.00002 | $0.00196 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 207 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Port provenance: adapted from the pinned upstream source at
984023ddac0d5e27624f2baacde6105e45de375funder MIT; see the repository parity ledger for the exact path and blob.
When this skill is invoked:
Parse the argument:
- No argument → full audit across all systems
[system-name]→ audit that single system only--summary→ summary table only, no file write
Phase 1 — Context Gathering
-
Read
design/gdd/systems-index.mdfor the full list of systems, their categories, and MVP/priority tier. -
L0 pre-scan: Before full-reading any GDDs, text search all GDD files for
## Summarysections plus common content-count keywords:text search pattern="(## Summary|N enemies|N levels|N items|N abilities|enemy types|item types)" glob="design/gdd/*.md" output_mode="files_with_matches"For a single-system audit: skip this step and go straight to full-read. For a full audit: full-read only the GDDs that matched content-count keywords. GDDs with no content-count language (pure mechanics GDDs) are noted as "No auditable content counts" without a full read.
-
Full-read in-scope GDD files (or the single system GDD if a system name was given).
-
For each GDD, extract explicit content counts or lists. Look for patterns like:
- "N enemies" / "enemy types:" / list of named enemies
- "N levels" / "N areas" / "N maps" / "N stages"
- "N items" / "N weapons" / "N equipment pieces"
- "N abilities" / "N skills" / "N spells"
- "N dialogue scenes" / "N conversations" / "N cutscenes"
- "N quests" / "N missions" / "N objectives"
- Any explicit enumerated list (bullet list of named content pieces)
-
Build a content inventory table from the extracted data:
System Content Type Specified Count/List Source GDD Note: If a GDD describes content qualitatively but gives no count, record "Unspecified" and flag it — unspecified counts are a design gap worth noting.
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.
- 6d ago First seen · 207 lines · 22 tokens per session scan A 4f944184f59c
content-audit is a skill published in the GitHub repository frabcd/codex-ai-game-studio (9 stars, last pushed 6d ago), licensed MIT. It adds 22 tokens to every session and 1,955 once invoked, about $0.0001 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 2026-08-31.
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