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 story-donegit 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/story-done)<a href="https://agentmods.dev/skills/frabcd/codex-ai-game-studio/story-done"><img src="https://agentmods.dev/badge/skills/frabcd/codex-ai-game-studio/story-done/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/story-done"><img src="https://agentmods.dev/badge/skills/frabcd/codex-ai-game-studio/story-done.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 | $0.00051 | $0.05239 |
| Opus 5 | $0.00026 | $0.02619 |
| Sonnet 5 | $0.00010 | $0.01048 |
| Haiku 4.5 | $0.00005 | $0.00524 |
Grade A, and why
story-done 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 8d 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
88% identical to story-done — 88 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 — 462 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.
Story Done
This skill closes the loop between design and implementation. Run it at the end of implementing any story. It ensures every acceptance criterion is verified before the story is marked done, GDD and ADR deviations are explicitly documented rather than silently introduced, code review is prompted rather than forgotten, and the story file reflects actual completion status.
Output: Updated story file (Status: Complete) + surfaced next story.
Phase 1: Find the Story
Resolve the review mode (once, store for all gate spawns this run):
- If
--review [full|lean|solo]was passed → use that - Else read
production/review-mode.txt→ use that value - Else → default to
lean
See the installed Codex role-gate protocol for the full check pattern.
If a file path is provided (e.g., $ai-game-studio:story-done production/epics/core/story-damage-calculator.md):
read that file directly.
If no argument is provided:
- Check
production/session-state/active.mdfor the currently active story. - If not found there, read the most recent file in
production/sprints/and look for stories marked IN PROGRESS. - If multiple in-progress stories are found, use
the available user-input mechanism:- "Which story are we completing?"
- Options: list the in-progress story file names.
- If no story can be found, ask the user to provide the path.
Phase 2: Read the Story
Read the full story file. Extract and hold in context:
- Story name and ID
- GDD Requirement TR-ID(s) referenced (e.g.,
TR-combat-001) - Manifest Version embedded in the story header (e.g.,
2026-03-10) - ADR reference(s) referenced
- Acceptance Criteria — the complete list (every checkbox item)
- Implementation files — files listed under "files to create/modify"
- Story Type — the
Type:field from the story header (Logic / Integration / Visual/Feel / UI / Config/Data) - Engine notes — any engine-specific constraints noted
- Definition of Done — if present, the story-level DoD
- Estimated vs actual scope — if an estimate was noted
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.
- 8d ago First seen · 462 lines · 51 tokens per session scan A 5250cc2be714
story-done is a skill published in the GitHub repository frabcd/codex-ai-game-studio (10 stars, last pushed 5d ago), licensed MIT. It adds 51 tokens to every session and 5,239 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to story-done, differing in 88 lines, and is treated as a copy.
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