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production-audit

production-audit is a skill for Claude Code, Codex from JunMystery/Agent-Guidance-Python. It costs 41 tokens per session (1,663 once invoked), scanned A, a copy of production-audit, MIT.

A local review of an application’s readiness for launch, based on evidence from the project files and deployment context.

In plain words
What is it for?
Use it before shipping, after a merge, or before a public launch to identify failures and fixes that should be addressed.
Why use it?
It helps find production risks that may remain even when automated tests pass or a feature has been merged.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 2repo 3mo ago A scan 41 tokens copy · 100% MIT

Good fit Use it before shipping, after a merge, or before a public launch to identify failures and fixes that should be addressed.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/junmystery/agent-guidance-python/production-audit
View source ↗ JunMystery/Agent-Guidance-Python
Install

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.

Any agent
npx skills add JunMystery/Agent-Guidance-Python --skill production-audit
Clone the repo
git clone --depth 1 https://github.com/JunMystery/Agent-Guidance-Python

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for production-audit

README.md
[![agentmods](https://agentmods.dev/badge/skills/junmystery/agent-guidance-python/production-audit/github.svg)](https://agentmods.dev/skills/junmystery/agent-guidance-python/production-audit)
Your own site
<a href="https://agentmods.dev/skills/junmystery/agent-guidance-python/production-audit"><img src="https://agentmods.dev/badge/skills/junmystery/agent-guidance-python/production-audit/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.

agentmods 80×15 button for production-audit

Your own site · 80×15
<a href="https://agentmods.dev/skills/junmystery/agent-guidance-python/production-audit"><img src="https://agentmods.dev/badge/skills/junmystery/agent-guidance-python/production-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,663 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00041 $0.01663
Opus 5.5 $0.00016 $0.00665
Sonnet 5.5 $0.00008 $0.00333
Haiku 4.5 $0.00004 $0.00166

Measured 2mo ago against content hash 54f769ac5ad4, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

production-audit 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.

Origin

This is a copy

100% identical to production-audit — 0 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.

skills/production-audit/SKILL.md · 207 lines

How it starts

The opening of the file, as written. The whole thing — 207 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Production Audit

Use this skill when the user asks whether an application is ready to ship, what could break in production, or what must be fixed before a launch. This is a maintainer-safe rewrite of the stale community production-audit idea: it keeps the useful production-readiness lens and removes unpinned external execution and third-party data sharing.

When to Use

  • The user asks "is this production-ready", "what would break in prod", "what did we miss", "audit this repo", or "ready to ship?"
  • A feature was merged and needs a pre-deploy or post-merge risk pass.
  • A public launch, demo, customer rollout, or investor walkthrough is close.
  • CI is green but the user wants production risk, not only test status.
  • A deployed URL, release branch, PR, or current checkout is available for evidence gathering.

When Not to Use

  • During active implementation when the right lens is line-level secure coding; use security-review first.
  • For pure libraries, templates, docs-only repos, or scaffolds unless the user wants packaging/release readiness rather than application readiness.
  • When the user asks for a formal compliance audit. This skill is engineering triage, not legal, financial, medical, or regulatory certification.
  • When the only available evidence is a product idea with no repo, deployment, CI, or runtime surface.

How It Works

Build the audit from local and user-authorized evidence. Do not run unpinned remote code, upload repository contents to third-party services, or call external scanners unless the user explicitly approves that specific tool and data flow.

Use this order:

  1. Establish the release surface.
  2. Read recent changes and current branch state.
  3. Inspect runtime, auth, data, payment, background-job, AI, and deployment boundaries that actually exist in the repo.
  4. Check CI, tests, migrations, environment documentation, and rollback path.
  5. Produce a short ship/block recommendation with specific fixes.

Evidence Checklist

Read the full file on GitHub · 207 lines

Changes

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.

  1. 2mo ago First seen · 207 lines · 41 tokens per session scan A 54f769ac5ad4

Subscribe to this mod's changes

production-audit is a skill published in the GitHub repository JunMystery/Agent-Guidance-Python (2 stars, last pushed 3mo ago), licensed MIT. It adds 41 tokens to every session and 1,663 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to production-audit, differing in 0 lines, and is treated as a copy.

DebuggingDevOps and cloudai-agentcoding-standardsmcp-serversoftware-development-workflow
Related

production-audit compared with skills from other repositories

production-audit next to 6 skills from other repositories
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production-auditJunMystery/Agent-Guidance-PythonSkill23mo agoMITA41Claude Code, Codex
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n8n-error-handlingczlonkowski/n8n-mcpSkill23kyesterdayMITA128Claude Code, Codex
n8n-validation-expertczlonkowski/n8n-mcpSkill23kyesterdayMITA91Claude Code, Codex
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analyze-dumpsvnscha/mcp-windbgSkill1.7k15d agoMITA56Claude Code
gcp-triagenirholas/three.wsSkill278todayApache-2.0A93Claude Code