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 Muriel-Salvan/x_aeon_agents --skill validating-production-qualitygit clone --depth 1 https://github.com/Muriel-Salvan/x_aeon_agentsWrote 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/muriel-salvan/x_aeon_agents/validating-production-quality)<a href="https://agentmods.dev/skills/muriel-salvan/x_aeon_agents/validating-production-quality"><img src="https://agentmods.dev/badge/skills/muriel-salvan/x_aeon_agents/validating-production-quality/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/muriel-salvan/x_aeon_agents/validating-production-quality"><img src="https://agentmods.dev/badge/skills/muriel-salvan/x_aeon_agents/validating-production-quality.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 | $0.00075 | $0.00875 |
| Opus 5.5 | $0.00030 | $0.00350 |
| Sonnet 5.5 | $0.00015 | $0.00175 |
| Haiku 4.5 | $0.00007 | $0.00088 |
Grade A, and why
validating-production-quality 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 2mo 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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Validating production quality
Sequential steps to be followed when using this skill
When validating production quality, follow those steps.
Create the validating-production-quality Execution Checklist (MANDATORY)
- Before executing anything, create a checklist named validating-production-quality Execution Checklist with all steps of these instructions.
- The validating-production-quality Execution Checklist must include all numbered steps explicitly.
- After completing each step of these instructions, mark the item in the validating-production-quality Execution Checklist as completed.
- Do not skip any item.
- If an item cannot be executed, explicitly explain why.
- Never mark the task as completed while any item from the validating-production-quality Execution Checklist remains open.
1. Inform the user
- Always tell the user "SKILL: I am validating production quality" to inform the user that you are running this skill.
2. Fix any potential regression
- Always run all test scenarios.
- Always fix all the failures that you see in the tests output.
For example, in a Python project:
python -m unittest
3. Update documentation
- Always use
skill: updating-docto update the project documentation.
4. Commit all pending modifications
- Always use
skill: committing-changesto commit all your changes in the current branch.
5. Sync the branch with its base
- Always use
skill: syncing-branch-with-baseto make sure the current branch is up-to-date with its base.
6. Remove any merge commit in the current branch
- Always check that there is no merge commit between the current branch and its base.
- If you find any merge commit, then always remove them by rebasing the branch in a linear way, using
cli: git rebase, and push again to the GitHub remote using--force-with-leaseoption.
Example, in case of merge commits found:
git log --oneline --ancestry-path github/main..my_branch
git rebase main
git push github --force-with-lease
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.
- 2mo ago First seen · 114 lines · 75 tokens per session scan A ee001df1f9b7
validating-production-quality is a skill published in the GitHub repository Muriel-Salvan/x_aeon_agents (2 stars, last pushed 3d ago), licensed BSD-3-Clause. It adds 75 tokens to every session and 875 once invoked, about $0.0003 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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