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 WildPigKing/codex-project-skill-manager --skill maintain-project-ai-recordsgit clone --depth 1 https://github.com/WildPigKing/codex-project-skill-managerWrote 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/wildpigking/codex-project-skill-manager/maintain-project-ai-records)<a href="https://agentmods.dev/skills/wildpigking/codex-project-skill-manager/maintain-project-ai-records"><img src="https://agentmods.dev/badge/skills/wildpigking/codex-project-skill-manager/maintain-project-ai-records/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/wildpigking/codex-project-skill-manager/maintain-project-ai-records"><img src="https://agentmods.dev/badge/skills/wildpigking/codex-project-skill-manager/maintain-project-ai-records.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 | $0.00043 | $0.00218 |
| Opus 5 | $0.00022 | $0.00109 |
| Sonnet 5 | $0.00009 | $0.00044 |
| Haiku 4.5 | $0.00004 | $0.00022 |
Grade A, and why
maintain-project-ai-records 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 11d 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.
What it actually says
Maintain Project AI Records
Run scripts/ensure_project_ai_records.py with the exact project root. The script creates missing files and never replaces existing content.
Do not run the script or append a milestone during a read-only request. Wait for a separately authorized writable task.
Read the resulting project AGENTS.md before continuing.
Store confirmed project-specific habits in AGENTS.md. Append milestone summaries to docs/ai/dev_log.md and unpromoted reusable lessons to docs/ai/experience_candidates.md.
Use at most six concise milestone bullets covering the goal, decisions, changes, verification, open issues, and reusable candidate when relevant. Do not log every command, credentials, private identifiers, or hidden reasoning.
Keep cross-project workflows out of project AGENTS.md. Promote experience to a user skill only after explicit satisfaction and authorization, using a separate workflow reflection.
What ships with it
2 files 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.
- 11d ago First seen · 19 lines · 43 tokens per session scan A 7bb245ea3ead
maintain-project-ai-records is a skill published in the GitHub repository WildPigKing/codex-project-skill-manager (22 stars, last pushed 15d ago), licensed MIT. It adds 43 tokens to every session and 218 once invoked, about $0.0002 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 2026-08-30.
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