accessibility
Design, implement, and audit accessible UI to WCAG 2.2 Level AA across Web, iOS, and Android…
Local-evidence production readiness audit for shipped apps, pre-launch reviews, post-merge checks, and "what breaks in prod?" questions without sending repo data to an external audit service. Use when auditing production readiness before launch, after a merge, or when asked what
$ npx -y skills add affaan-m/ECC --skill production-audit --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/production-auditContext preview
The summary Claude sees to decide when to auto-load this skill.
Local-evidence production readiness audit for shipped apps, pre-launch reviews, post-merge checks, and "what breaks in prod?" questions without sending repo data to an external audit service. Use when auditing production readiness before launch, after a merge, or when asked what
name: production-audit description: Local-evidence production readiness audit for shipped apps, pre-launch reviews, post-merge checks, and "what breaks in prod?" questions without sending repo data to an external audit service. Use when auditing production readiness before launch, after a merge, or when asked what breaks in prod. metadata: origin: community
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.
did we miss", "audit this repo", or "ready to ship?"
evidence gathering.
use `security-review` first.
wants packaging/release readiness rather than application readiness.
triage, not legal, financial, medical, or regulatory certification.
CI, or runtime surface.
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.
Start with cheap, local signals:
git status --short --branch git log --oneline --decorate -20 git diff --stat origin/main...HEAD
Then inspect the project-specific surface:
manifests.
database migrations.
If a deployed URL is in scope, use browser or HTTP checks only against that URL and avoid credentialed actions unless the user supplies a safe test account.
files?
where the app needs them?
untrusted content crossing into privileged actions?
tenancy model?
submission states?
happened?
Use scores to force prioritization, not to imply mathematical certainty.
| Band | Score | Meaning | | --- | --- | --- | | Blocked | 0-49 | Do not ship until the top risks are fixed | | Risky | 50-69 | Ship only behind a small rollout or internal beta | | Launchable With Caveats | 70-84 | Ship if owners accept the listed risks | | Strong | 85-100 | No obvious launch blockers from available evidence |
Cap the score at `69` if any of these are true:
Cap the score at `84` if CI is not green or the launch-critical path was not tested end to end.
Lead with one sentence:
Production audit: 76/100, launchable with caveats, with webhook idempotency and rollback docs as the two risks to fix before public launch.
The
Your agent can write code, but ECC gives it a coordinated engineering system and toolbox: it plans before it builds, verifies changes with tests, reviews its own work from a fresh context, remembers what matters, and turns repeated wins into reusable skills
Repo: affaan-m/ECC
Design, implement, and audit accessible UI to WCAG 2.2 Level AA across Web, iOS, and Android…
Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for…
Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks…
Design and optimize AI agent action spaces, tool definitions, and observation formatting for…
Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained…
Use after completing any non-trivial task. The agent self-rates its output on 5 axes —…