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/striderza/opencodegamestudios/content-auditnpx skills add striderZA/OpenCodeGameStudios --skill content-auditgit clone --depth 1 https://github.com/striderZA/OpenCodeGameStudiosWrote 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/striderza/opencodegamestudios/content-audit)<a href="https://agentmods.dev/skills/striderza/opencodegamestudios/content-audit"><img src="https://agentmods.dev/badge/skills/striderza/opencodegamestudios/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 | $0.00022 | $0.01833 |
| Opus 5 | $0.00011 | $0.00916 |
| Sonnet 5 | $0.00004 | $0.00367 |
| Haiku 4.5 | $0.00002 | $0.00183 |
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 yesterday.
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
98% identical to content-audit — 1 line 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 — 205 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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, Grep all GDD files for
## Summarysections plus common content-count keywords:Grep 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.
Phase 2 — Implementation Scan
For each content type found in Phase 1, scan the relevant directories to count what has been implemented. Use Glob and Grep to locate files.
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.
- yesterday First seen · 205 lines · 22 tokens per session scan A 295891c26032
content-audit is a skill published in the GitHub repository striderZA/OpenCodeGameStudios (84 stars, last pushed 24d ago), licensed MIT. It adds 22 tokens to every session and 1,833 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to content-audit, differing in 1 line, and is treated as a copy.
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