production-readiness

production-readiness is a skill for Claude Code, Codex from Nordic-AI/production-readiness-skills. It costs 110 tokens per session (3,205 once invoked), scanned A, original, Apache-2.0.

A coordinated review of whether an application is ready to run in production, meaning the live environment used by real users. It delegates checks to specialists and combines their findings into one report.

In plain words
What is it for?
Use it when asking whether an app is ready to ship, what is missing before launch, or how to prepare it for production.
Why use it?
It gives teams a single view of important launch gaps instead of requiring separate reviews for security, testing, reliability, accessibility, compliance, and other areas.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions CLAUDE.md.

Good fit Use it when asking whether an app is ready to ship, what is missing before launch, or how to prepare it for production.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/nordic-ai/production-readiness-skills/production-readiness
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 Nordic-AI/production-readiness-skills --skill production-readiness
Clone the repo
git clone --depth 1 https://github.com/Nordic-AI/production-readiness-skills

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-readiness

README.md
[![agentmods](https://agentmods.dev/badge/skills/nordic-ai/production-readiness-skills/production-readiness/github.svg)](https://agentmods.dev/skills/nordic-ai/production-readiness-skills/production-readiness)
Your own site
<a href="https://agentmods.dev/skills/nordic-ai/production-readiness-skills/production-readiness"><img src="https://agentmods.dev/badge/skills/nordic-ai/production-readiness-skills/production-readiness/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-readiness

Your own site · 80×15
<a href="https://agentmods.dev/skills/nordic-ai/production-readiness-skills/production-readiness"><img src="https://agentmods.dev/badge/skills/nordic-ai/production-readiness-skills/production-readiness.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 110 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,205 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 original No closer match found 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 $0.00110 $0.03205
Opus 5 $0.00055 $0.01603
Sonnet 5 $0.00022 $0.00641
Haiku 4.5 $0.00011 $0.00320

Measured 12d ago against content hash 0e9d596620d2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

production-readiness 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 12d 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.

skills/production-readiness/SKILL.md · 281 lines

How it starts

The opening of the file, as written. The whole thing — 281 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Production Readiness Orchestrator

You are the entry point for a full production-readiness review. Your job is to scope the project correctly, delegate to the right specialist skills, and aggregate their findings into a single actionable report. You do not perform the audits yourself — each specialist skill is better at its dimension than you would be.

When to run

Trigger when the user:

  • Explicitly invokes /production-readiness
  • Asks whether an app is "ready for production", "ready to ship", "ready to launch"
  • Asks for a general audit without specifying a dimension
  • Asks what's "missing" before going live

If the user asks about a specific dimension (e.g. "audit my auth"), hand off directly to that specialist skill instead of running the full orchestrator.

Mode detection

Determine the current mode before anything else:

  • Plan mode — you can read but not edit. Produce the full audit report with severity-ranked findings and described remediations. Do not attempt to apply fixes.
  • Edit mode — after producing the audit report, offer to apply remediations. Ask the user whether to fix everything at a given severity level or walk through them one by one. Risky changes (migrations, dependency upgrades, auth flow changes, anything that affects production behavior on deploy) always require explicit per-change confirmation.

State the detected mode at the top of the run so the user can correct you.

Step 1 — scoping

Ask the user these questions in a single batched prompt. Keep it short. Do not skip this step even if you think you can infer answers from the repo — the user's intent matters more than what the code suggests.

Before I run the review, I need to scope it:

1. **Scope tier** — how critical is this?
   - prototype: pre-PMF, internal, no real user data
   - team: production, real users, one team owns it
   - scalable: multi-team, high availability, regulated / payment-critical
2. **Jurisdiction** — where does the product operate, and where do users live?
   (EU-first, but I'll adapt. Tell me countries or "unknown".)
3. **Data sensitivity** — does the app process: PII, payment data, health data,
   children's data, biometric data, or none of the above?
4. **Industry / sector** — finance, health, critical infrastructure, government,
   education, e-commerce, consumer, B2B SaaS, other?
5. **Deployment target** — cloud (which?), on-prem, hybrid, edge, mobile client?
6. **Anything I should skip?** — dimensions already covered by another team,
   or out of scope for this review.

Read the full file on GitHub · 281 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. 12d ago First seen · 281 lines · 110 tokens per session scan A 0e9d596620d2

Subscribe to this mod's changes

production-readiness is a skill published in the GitHub repository Nordic-AI/production-readiness-skills (2 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 110 tokens to every session and 3,205 once invoked, about $0.0006 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 2026-08-31.

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