Common Review Policy logo

Common Review Policy

Community
HoangNguyen0403
common-review-policy

Define a repository review policy fixing what each review pass checks, how severities rank, which paths are skipped, the nit cap, and who approves. Use when review findings feel inconsistent or noisy, or when tuning an automated reviewer.

Overview

PublisherHoangNguyen0403
Repositoryagent-skills-standard
Skill namecommon-review-policy
Stars
573
Forks
166
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

    Published by HoangNguyen0403 on GitHub. Read the source before you install it.

Installation

Install the Common Review Policy 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/HoangNguyen0403/agent-skills-standard/tree/develop/.agents/skills/common/common-review-policy
  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/HoangNguyen0403/agent-skills-standard.git /tmp/agent-skills-standard
mkdir -p .claude/skills
cp -r /tmp/agent-skills-standard/.agents/skills/common/common-review-policy .claude/skills/common-review-policy
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Common Review Policy 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 Common Review Policy 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 Common Review Policy 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.

Review Policy Standard

Priority: P1 (HIGH)

Every pull request gets the same passes in the same order. A review that varies by reviewer or by day is not a control.

1. The Policy File

  • Location: docs/review-policy.md, tracked in the repository and reviewed like code.
  • code-review and review-ticket load it when present; its severity and skip rules override their defaults.
  • Owned by the technical lead. Absent the file, the workflow defaults apply and the review says so.
  • Load references/review-policy-template.md when drafting or auditing the file.

2. Required Passes

Declare the passes and their order. Each pass names what it checks and what it explicitly ignores.

PassChecksOut of scope
Correctnesslogic, edge cases, requirement coveragestyle
Securityinjection, secrets, authorization, trust boundariestheoretical risk with no path
Testsnew logic covered, failure paths assertedcoverage percentage targets
Complianceaudit, data classification, licenceproduct decisions

3. Severity Ladder

  • Blocker: merge causes a defect, breach, or data loss. Concrete path required.
  • Major: real risk or requirement gap the author must resolve or explicitly accept.
  • Nit: everything else, including style, naming, and preference. Minor and Suggestion collapse into Nit.
  • Confidence: a finding without evidence is needs validation, never a silent drop and never a Blocker.
  • One ladder per repository. Workflows that use a longer list map onto these three before publishing.

4. Noise Control

  • Skip list: generated code, vendored dependencies, lockfiles, and snapshots. Name them as globs.
  • Nit cap: a fixed maximum per review. Over the cap, keep the highest-signal nits and drop the rest.
  • Lead with risk: Blocker and Major first, nits last, praise never.
  • Deduplicate by root cause: one finding per cause, listing the affected locations.

5. Tuning and Feedback

  • Review the policy monthly: rate a sample of findings as useful or noise, then adjust cap, skip list, and pass scope.
  • Recurring Blockers mean a missing standard. Route them to retro-learn so the preventing skill and its evals absorb the rule.
  • Record each tuning change in the policy file so severity drift is visible.

6. Separation of Duties

  • The agent reviews and proposes; a human approves. The agent never approves its own change.
  • Approval is enforced by branch protection, not by the reviewing agent's verdict.
  • Publishing findings to a ticket or pull request needs operator approval, and never happens from untrusted review context.

Anti-Patterns

  • No per-reviewer severity: One ladder, defined in the policy file.
  • No unbounded nits: Cap them and keep the highest signal.
  • No reviewing generated code: Put it in the skip list.
  • No Blocker without a path: Downgrade to needs validation.
  • No agent self-approval: A human approves through branch protection.
  • No silent policy drift: Record every tuning change in the file.

Red Flags

  • Stop if the review opens with praise: Lead with Blocker and Major findings.
  • Stop if the same Blocker recurs across reviews: Route it to retro-learn instead of re-reporting it.
  • Stop if severity is chosen to force attention: Rank by consequence, not by urgency.

References

Canonical response anchors

When this skill applies, preserve the following domain terminology or equivalent concrete examples in the answer when relevant:

  • docs/review-policy.md
  • Blocker, Major, Nit
  • skip list
  • nit cap
  • needs validation
  • monthly tuning
  • branch protection

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 Common Review Policy AI skill do?

Define a repository review policy fixing what each review pass checks, how severities rank, which paths are skipped, the nit cap, and who approves. Use when review findings feel inconsistent or noisy, or when tuning an automated reviewer.

Why use Common Review Policy on TypingMind?

Because you install it once and use it with any model. Common Review Policy 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 Common Review Policy in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/HoangNguyen0403/agent-skills-standard/tree/develop/.agents/skills/common/common-review-policy. 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 Common Review Policy?

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 Common Review Policy?

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

Is the Common Review Policy AI skill free?

Yes. It is published on GitHub by HoangNguyen0403 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇