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 changeloggit 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/changelog)<a href="https://agentmods.dev/skills/frabcd/codex-ai-game-studio/changelog"><img src="https://agentmods.dev/badge/skills/frabcd/codex-ai-game-studio/changelog/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/changelog"><img src="https://agentmods.dev/badge/skills/frabcd/codex-ai-game-studio/changelog.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00029 | $0.01506 |
| Opus 5.5 | $0.00012 | $0.00602 |
| Sonnet 5.5 | $0.00006 | $0.00301 |
| Haiku 4.5 | $0.00003 | $0.00151 |
Grade A, and why
changelog 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 1mo 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 — 177 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 1: Parse Arguments
Read the argument for the target version or sprint number. If a version is given, use the corresponding git tag. If a sprint number is given, use the sprint date range.
Verify the repository is initialized: run git rev-parse --is-inside-work-tree to confirm git is available. If not a git repo, inform the user and abort gracefully.
Phase 2: Gather Change Data
Read the git log since the last tag or release:
git log --oneline [last-tag]..HEAD
If no tags exist, read the full log or a reasonable recent range (last 100 commits).
Read sprint reports from production/sprints/ for the relevant period to understand planned work and context behind changes.
Read completed design documents from design/gdd/ for any new features implemented during this period.
Phase 3: Categorize Changes
Categorize every change into one of these categories:
- New Features: Entirely new gameplay systems, modes, or content
- Improvements: Enhancements to existing features, UX improvements, performance gains
- Bug Fixes: Corrections to broken behavior
- Balance Changes: Tuning of gameplay values, difficulty, economy
- Known Issues: Issues the team is aware of but have not yet resolved
- Miscellaneous: Changes that do not fit the above categories, or commits whose messages are too vague to classify confidently
For each commit, check whether the message contains a task ID or story reference
(e.g. [STORY-123], TR-, #NNN, or similar). Count commits that lack any task reference
and include this count in the Phase 4 Metrics section as: Commits without task reference: [N].
Phase 4: Generate Internal Changelog
# Internal Changelog: [Version]
Date: [Date]
Sprint(s): [Sprint numbers covered]
Commits: [Count] ([first-hash]..[last-hash])
## New Features
- [Feature Name] -- [Technical description, affected systems]
- Commits: [hash1], [hash2]
- Owner: [who implemented it]
- Design doc: [link if applicable]
## Improvements
- [Improvement] -- [What changed technically and why]
- Commits: [hashes]
- Owner: [who]
## Bug Fixes
- [BUG-ID] [Description of bug and root cause]
- Fix: [What was changed]
- Commits: [hashes]
- Owner: [who]
## Balance Changes
- [What was tuned] -- [Old value -> New value] -- [Design intent]
- Owner: [who]
## Technical Debt / Refactoring
- [What was cleaned up and why]
- Commits: [hashes]
## Miscellaneous
- [Change that didn't fit other categories, or vague commit message]
- Commits: [hashes]
## Known Issues
- [Issue description] -- [Severity] -- [ETA for fix if known]
## Metrics
- Total commits: [N]
- Files changed: [N]
- Lines added: [N]
- Lines removed: [N]
- Commits without task reference: [N]
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.
- 1mo ago First seen · 177 lines · 29 tokens per session scan A df817521d10b
changelog is a skill published in the GitHub repository frabcd/codex-ai-game-studio (17 stars, last pushed 6d ago), licensed MIT. It adds 29 tokens to every session and 1,506 once invoked, about $0.0001 per session on Opus 5.5. 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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