Readme Review logo

Readme Review

Organization
navikt
readme-review

Strukturell gjennomgang og generering av README-er tilpasset prosjekttype — tjeneste, bibliotek, monorepo eller naisjob

Overview

Publishernavikt
Repositorycopilot
Skill namereadme-review
Stars
60
Forks
16
Bundled files
7
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 7 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by navikt on GitHub. Read the source before you install it.

Installation

Install the Readme Review AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/navikt/copilot/tree/main/skills/readme-review
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/navikt/copilot.git /tmp/copilot
mkdir -p .claude/skills
cp -r /tmp/copilot/skills/readme-review .claude/skills/readme-review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Readme Review in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Readme Review on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Readme Review is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

README Review & Scaffold

Structural review and generation of READMEs adapted to project type. Complements @forfatter (language quality) with structural guidance (what sections, what order, what depth).

Workflow

Step 0: Detect README scope
Step 1: Route → review or generate
Step 2a: Review existing README
Step 2b: Generate new README
Step 3: Hand off language issues to @forfatter

Step 0: Detect README scope

Before reviewing or generating, determine what kind of README this is. Use file location and nearby manifests:

ScopeSignalsExample
Monorepo rootRoot README.md, multiple apps/ or packages/, workspace confignavikt/fp-sak/README.md with apps/ dir
Service / API.nais/ dir, main.go / Application.kt, Dockerfileapps/my-service/README.md
Library / packagePublished to npm/Maven, no .nais/, exports public APIlibs/shared-utils/README.md
Naisjob.nais/naisjob.yaml, scheduled execution, no HTTP endpointsapps/batch-processor/README.md
Docs-onlyNo source code, only markdown filesdocs/README.md

If scope is unclear, ask the user.

Step 1: Route

  • Existing README + user says "review", "check", "improve" → Step 2a
  • No README or user says "create", "scaffold", "generate" → Step 2b
  • Ambiguous → check if README.md exists in the target directory

Step 2a: Review existing README

2a.1 Check sections against spec

Read the existing README. For each section in the spec for this project type (see section-spec.md):

StatusMeaning
✅ OKSection exists with substantive content
⚠️ WeakSection exists but is thin, outdated, or misplaced
❌ MissingRequired section is absent
—Section not applicable for this project type

2a.2 Check for anti-patterns

Scan for structural anti-patterns (see anti-patterns.md). Flag only patterns that are actually present.

2a.3 Output

markdown
## README review — {project name}

**Scope:** {service / library / monorepo / naisjob}

### Section check

| Section | Status | Notes |
|---------|--------|-------|
| Title + one-liner | ✅ | — |
| Quick start | ❌ | No runnable commands found |
| ... | ... | ... |

### Anti-patterns found

- **{Pattern name}**: {One-sentence description of what's wrong and how to fix it}

### Top 3 fixes

1. {Most impactful fix}
2. {Second fix}
3. {Third fix}

Surface top 3 fixes ordered by impact. Don't overwhelm with minor issues.

Step 2b: Generate new README

  1. Pick template from references/ based on detected scope
  2. Fill in what you can detect from the codebase:
    • Project name (from directory or manifest)
    • Tech stack (from go.mod, package.json, build.gradle.kts)
    • Build/test commands (from Makefile, .mise.toml, package.json scripts)
    • Endpoints (from route definitions)
    • Config (from environment variable usage)
  3. Mark remaining placeholders with {TODO: description}
  4. Output the draft README

Templates: service · library · monorepo · naisjob

Step 3: Language handoff

After structural review or generation, if the text has language issues (AI markers, passive voice, anglicisms), suggest:

For language polish, use @forfatter or the klarsprak skill.

Do not duplicate @forfatter's work. This skill handles structure; @forfatter handles language.

Principles

Cognitive funneling

Structure README from broad to specific. Readers scan top-down and bail when they have enough information:

  1. Title + one-liner — what is this? (< 120 characters)
  2. Quick start — how do I run it? (copy-paste commands)
  3. Details — API, config, architecture
  4. Meta — contributing, license, team

"Your documentation is complete when someone can use your module without ever having to look at its code." — Ken Williams

README is the front door

README should orient and get people started. Deep content belongs elsewhere:

In READMEIn external docs
One-liner descriptionFull architecture docs
Quick start commandsDetailed runbooks
Config table (env vars)ADRs, threat models
API overview or linkFull OpenAPI spec
Team + Slack channelIncident response procedures

Code over prose

markdown
# ❌ Prose
You can start the development server by running the development command
using the mise task runner.

# ✅ Code
mise dev

Fewer sections = less drift

Only include sections you will maintain. An empty "## Roadmap" is worse than no roadmap section. README rots faster than code.

Boundaries

✅ Always

  • Detect project scope before suggesting sections
  • Check for missing quick start (most common gap)
  • Use Missing/Weak/OK status, not numeric scores
  • Surface top 3 fixes, not an exhaustive list

⚠️ Ask first

  • Rewriting large sections of an existing README
  • Removing sections that may have historical context
  • Changing README language (Norwegian ↔ English)

🚫 Never

  • Duplicate content from AGENTS.md into README
  • Dump full runbooks, security policies, or ADRs into README
  • Add numeric scores or gamified ratings
  • Rewrite prose style (that's @forfatter's job)

Related

ResourceUse for
@forfatterDeeper editorial pass on an existing text
klarsprak skillNorwegian language wash: klarspråk, AI markers, anglicisms, fagtermer
nav-architecture-review skillADR generation (link from README, don't inline)
mcp-onboardingAgent readiness assessment and AGENTS.md generation

Sources

Review contract

Axes: the section check (2a.1) and the anti-pattern scan (2a.2). The block below closes the Step 2a report.

The review ends here, in this shape. A review with no output section has not run.

Judge primary evidence. The diff, the file, the EXPLAIN output, the rendered page — never your own summary of the change, and never your memory of what you meant to write. Resolve the base first, then cover committed, staged, unstaged and untracked changes. Read untracked files in full: diff output omits them.

Every axis reports. Each axis produces at least one finding, or one line saying what it inspected and what that evidence does not prove. An axis that says nothing has not looked.

Report what you inspected. "No findings in the two files I opened" and "no findings in the change" are different claims, and only the first one is ever true.

Inspected:     <files, queries, URLs, viewports actually opened>
Not inspected: <in scope, not examined, and why>
Findings:      <n blocking, n concerns>
Verdict:       BLOCK | CONCERNS | CLEAN
  • BLOCK — at least one finding that, shipped as written, risks data loss, a security or privacy breach, a production incident, or a wrong answer to a user.
  • CONCERNS — no blocking finding, but at least one a maintainer should fix or answer first.
  • CLEAN — every axis inspected against primary evidence, nothing at either bar. CLEAN claims only the axes above and the files on the Inspected line, and it is wrong if a defect is later found in them.

Not a review: LGTM; restating what the change does; cosmetic findings only; reading the changed lines without the code they call.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Readme Review AI skill do?

Strukturell gjennomgang og generering av README-er tilpasset prosjekttype — tjeneste, bibliotek, monorepo eller naisjob

Why use Readme Review on TypingMind?

Because you install it once and use it with any model. Readme Review is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Readme Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/navikt/copilot/tree/main/skills/readme-review. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Readme Review?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Readme Review?

As many as you like. As long as a model supports skills, you can use Readme Review with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Readme Review AI skill free?

Yes. It is published on GitHub by navikt under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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