Expertise·Developer Tools & Repos·v1.1.0

production Agent Skill

Autonomous production readiness audit for software products.

Context cost
4.2k tokensestimated from the bundle, loaded when it triggers
Bundle
1 file · 16.9 kBtext throughout, nothing executable
Licence
MITthe author’s own terms
Last change
12 days agov1.1.0
Servers it uses
Noneruns standalone

What it does

Autonomous production readiness audit for software products.

What this skill changes about the agent has not been set out here as a list. Its SKILL.md, shown below, says it in the author’s own words.

Expertise

Domain judgement the base model does not have.

The skill itself

A skill is instructions the model reads, so you can see what you are getting: below is the start of its SKILL.md. The front matter loads with every session, the body loads when the skill triggers, and the whole file comes with the install.

SKILL.md16.9 kB · preview
--- name: production license: MIT metadata: author: miisodev version: "1.1.0" ---
10# Production readiness
11
12An autonomous audit that answers one question with evidence: **can this product face real users now, and if not, what stands in the way?** It runs start to finish without stopping to ask, covers every surface and every applicable part of the product, and returns a structured payload plus a report. The report ranks each part and each surface by risk and gives a go/no-go decision for each surface and for the whole product.
13
14The skill is independent of stack, vendor, region and agent harness. Tools and vendors named in the references are examples. Use what the project actually runs on.
15
16## How the run works
17
18This is designed to be one long, thorough run. Work through the phases below until every applicable check has a recorded result, then produce the deliverables. Do not stop partway to ask questions. When something is ambiguous, make the most reasonable assumption, record it in run.assumptions, and continue. A wrong assumption stated plainly is easy for the owner to correct. A run that stops halfway gives them nothing.
19
201. **Scope.** Choose the profile from the request (table below); default to **Pre-Launch Gate** for an unlaunched product and **Full Audit** for a live one. Establish what the product is, who uses it and where (product.markets drives privacy, tax, accessibility and consumer law), and what environments you can reach. Record supported runtime/platform/protocol versions and deployment ownership, including self-hosted, offline or disconnected promises. Then reconnoitre the project for its stated intent, wherever it lives and whatever it is called: a blueprint, PRD, spec, business plan, brand brief, agent instruction files (AGENTS.md, CLAUDE.md, GEMINI.md and the like, which often point at the rest), READMEs, docs, the pricing page and store listings. Assume no folder or file name. Record in run.assumptions what you found and used, and where. The strongest statement of requirements found is the standard for the functional part; statements of pricing, brand and stack inform billing, cost, brand and infrastructure. Where there is none, derive the standard from the product's public claims.
212. **Inventory surfaces.** Read references/product-routing.md to map the product and deployment model to applicable parts; product labels are starting points, never exclusions. Find every surface the product exposes (catalogue below) from the repository, deploy configuration, DNS, app manifests, package manifests and docs. Record each in surfaces with a stable id, and mark which are core.
223. **Decide applicability.** Select from behavior and trust boundaries: an MCP server can need MCP checks without calling a model, a local app can need data/recovery checks without a backend, and an internal tool can need security/accessibility without billing or SEO. For each of the 39 parts, decide whether it applies. Record every part that does not apply in parts with the reason. Anything not declared inapplicable must be assessed.
234. **Gather evidence.** Automated evidence first: run the project's own build, tests, linters and scanners, then the checks each reference lists. Then manual evidence: read code, walk journeys, probe endpoints and inspect pages, within the safety limits below. Each part's reference file lists its evidence sources.
245. **Assess every check.** For each applicable part, read its reference file and record a result for **every** check on every surface it applies to: pass, partial, fail, not_verified or not_applicable (with the reason in evidence). Omitting a check hides a gap. Apply the part's severity notes to set severity, and set core_flow: true where the check protects authentication, payment, the primary value action or data integrity. Add custom checks (SEC-C01) for risks the references do not cover.
256. **Write findings.** Every failing or partial check of Critical or High severity belongs to a finding, and lower-severity ones can be grouped into findings too. Findings carry evidence, user and business impact, a specific recommendation, effort (S/M/L), an owner ("unassigned" unless one is known; never invent names) and how the fix will be validated. Write the executive summary last.
267. **Score and render.** Save the payload as production-readiness.json in the output folder (below) and run python <this skill's directory>/scripts/readiness.py <output folder>/production-readiness.json. The script validates the payload and warns about checks you skipped. It computes scores, coverage, risk rankings and decisions, and writes production-readiness.md and production-readiness.result.json. Fix any errors and act on the warnings, then run it again.
278. **Return.** Reply with the decision, the top blockers, the items that must be verified by a person, the surface and part rankings (the top of each table is enough), and the paths to the report and payload.
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This is a preview of SKILL.md. Download or install the skill to get the whole thing.
In the file
SKILL.md2,521 words
Files1
LicenceMIT
Why you can read it

Nothing in a skill executes. The client loads the text and the model follows it, so a skill can be audited the way a runbook is — by reading it.

What it costs in context

Skills are not billed by the call. They are paid for in context: every token the instructions occupy is a token your code, your diff and your conversation cannot use. Here is what this one takes and when it takes it.

≈190
always loaded
The name and description, so the model knows the skill exists and when to reach for it.
4,035
on trigger
The instruction body, read only when the skill fires.
2.1%
of a 200k window
Ten skills this size would take about 21% of the window before you open a file.
050k100k150k200k context window

4.2k tokens, estimated from the bundle at four bytes to the token, held for the rest of the session once it triggers. Heavy. Teams tend to install this one per project rather than globally, and load it only when the job comes up.

Servers bill, skills cost

A server charges by the month. A skill charges once per session, in context, and then keeps charging it for as long as the session lives.

Before and after

The same question, put to the same model twice: once as it comes, and once with these instructions loaded.

No worked example has been published for this skill yet.

The procedure it runs

The procedure has not been set out here step by step. It is in the body of its SKILL.md: the start of it is shown above, and the whole file comes with the install.

Prose, not code

These steps are written for a model to follow, not executed by a runtime. It can still be told to skip one, and it will say so when it does.

Servers it uses

None. This skill calls no MCP servers at all.

Everything it needs is in the instructions, so it works in a project with nothing connected — the model reads the file and changes how it works with what it can already reach.

Its SKILL.md does not declare which tools it asks the agent for, so what it touches is whatever the instructions themselves ask for — read them before you install it.

What it asks for
Writes filesnot declared
Network accessnot declared

This SKILL.md carries no allowed-tools line, so neither is declared. A skill grants no permissions of its own — it can only ask for tools your client already has.

What it will not do

Every skill is narrow, and the useful ones say where they stop. These are the jobs this one is the wrong tool for.

What this skill is not for has not been published here. Nothing is implied by that: it is a section the author has not filled in.

What is in the bundle

1 file, 16.9 kB on disk. A bundle is text throughout: the instructions the model reads, plus the templates it fills in.

  • SKILL.md16.9 kB
What is not in it

No dependencies and nothing executable: a skill is text the agent reads, so the bundle is 1 file you can review in full before installing. The MIT licence covers the templates and examples as well as the instructions.

Install

Installing copies the bundle into your project. Nothing runs at install time — the files sit on disk until the model reads them.

# production · 4.2k tokens when loaded · macOS, Linux mkdir -p .claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/production/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/production" ] && { [ ! -e .claude/skills/production ] || { mv .claude/skills/production "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/production" .claude/skills/ && echo "Installed .claude/skills/production"
On Windows, or any OS with Node 20+
npx mcprush@latest skill add miisodev/production

Windows PowerShell says 'running scripts is disabled on this system'? Run Set-ExecutionPolicy -Scope CurrentUser RemoteSigned once, or type npx.cmd instead of npx (codex.cmd, gemini.cmd, grok.cmd likewise). PowerShell 7 needs neither. Writes to .claude/skills/production/ in the current project. For every project instead, run mkdir -p ~/.claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/production/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/production" ] && { [ ! -e ~/.claude/skills/production ] || { mv ~/.claude/skills/production "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/production" ~/.claude/skills/ && echo "Installed ~/.claude/skills/production" (macOS, Linux) — or add --global to the npx line. The curl line replaces .claude/skills/production/ only after the download succeeds, so files left there by another skill of the same name, or by an older release, do not mix in. A copy already there is moved aside, not deleted, and the line prints where.

Which clients pick it up on their own

A skill is a folder of text. Most of these read a skills folder and pick it up without being told; the rest take the same folder another way — an upload in the app, a parameter on an API call — and then choose it by its description just the same.

Claude Code.claude/skills/
Claude DesktopCustomize › Skills
ChatGPTSkills › Create › Upload
Cursor.cursor/skills/
VS Code.github/skills/
Codex CLI.agents/skills/
Gemini CLI.gemini/skills/
Grok Build.grok/skills/
Microsoft CopilotSkills › Upload a skill
PerplexityComputer › Skills › Upload a skill
DeepSeek Harness.dsh/skills/
Zed.agents/skills/
Devin Desktop.devin/skills/
Windsurf (legacy).windsurf/skills/
OpenAI Agents SDKInstructions or sandbox Skills
HTTP / APIa request parameter
This release
Version1.1.0
Published12 days ago
PriceFree
Referencemiisodev/production

Versions

v1.1.0 shipped 12 days ago. Instructions change more often than APIs do — a skill can be rewritten entirely without anything it depends on moving.

v1.1.0
20 Oct 2026
  • v1.1.0 — Broader production coverage
v1.0.1
20 Oct 2026
  • The version this listing went live with, after review.
Pinning

The install command always fetches the release that is current the day you run it — v1.1.0 today — and cannot ask for an earlier one. The copy on your disk does not change until you run it again.

Reviews

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Anybody with an account, one review each. It carries the version that was current when you wrote it, and the publisher may reply once.

Who wrote it

MI
miisodev

Wassup you can call me Miiso, I like learning, innovating and exploration.

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