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 frabcd/codex-ai-game-studio --skill design-reviewgit 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/design-review)<a href="https://agentmods.dev/skills/frabcd/codex-ai-game-studio/design-review"><img src="https://agentmods.dev/badge/skills/frabcd/codex-ai-game-studio/design-review/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/frabcd/codex-ai-game-studio/design-review"><img src="https://agentmods.dev/badge/skills/frabcd/codex-ai-game-studio/design-review.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 | $0.00034 | $0.03357 |
| Opus 5 | $0.00017 | $0.01679 |
| Sonnet 5 | $0.00007 | $0.00671 |
| Haiku 4.5 | $0.00003 | $0.00336 |
Grade A, and why
design-review 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.
This is a copy
86% identical to design-review — 50 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 — 271 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.
Phase 0: Parse Arguments
Extract --depth [full|lean|solo] if present. Default is full when no flag is given.
Note: --depth controls the analysis depth of this skill (how many specialist agents are spawned). It is independent of the global review mode in production/review-mode.txt, which controls director gate spawning. These are two different concepts — --depth is about how thoroughly this skill analyses the document.
full: Complete review — all phases + specialist agent delegation (Phase 3b)lean: All phases, no specialist agents — faster, single-session analysissolo: Phases 1-4 only, no delegation, no Phase 5 next-step prompt — use when called from within another skill
Phase 1: Load Documents
Read the target design document in full. Read AGENTS.md to understand project context and standards. Read related design documents referenced or implied by the target doc (check design/gdd/ for related systems).
Dependency graph validation: For every system listed in the Dependencies section, use file discovery to check whether its GDD file exists in design/gdd/. Flag any that don't exist yet — these are broken references that downstream authors will hit.
Lore/narrative alignment: If design/gdd/game-concept.md or any file in design/narrative/ exists, read it. Note any mechanical choices in this GDD that contradict established world rules, tone, or design pillars. Pass this context to game-designer in Phase 3b.
Prior review check: Check whether design/gdd/reviews/[doc-name]-review-log.md exists. If it does, read the most recent entry — note what verdict was given and what blocking items were listed. This session is a re-review; track whether prior items were addressed.
Phase 2: Completeness Check
Evaluate against the Design Document Standard checklist:
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.
- 10d ago First seen · 271 lines · 34 tokens per session scan A 7c2bcf2e2117
design-review is a skill published in the GitHub repository frabcd/codex-ai-game-studio (10 stars, last pushed 2d ago), licensed MIT. It adds 34 tokens to every session and 3,357 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to design-review, differing in 50 lines, and is treated as a copy.
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