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Agents40k · #4980

acreadiness-policy

Enables your agent to help define or apply policies for AI project assessment. It's useful for standardizing how projects are evaluated and ensuring compliance.

What it does

This tool helps create and apply custom rules to assess your code quality. You can define which checks are important, which to ignore, and the minimum acceptable score.

When to use it

  • ✓When you want to ignore some quality checks.
  • ✓When you want to set a minimum score to approve code.
  • ✓When you want to standardize quality rules across your organization.

Example of what to ask your AI

“How can I create a rule that ignores the 'documentation' check and requires the 'readme' to have high importance?”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/github/awesome-copilot/blob/main/skills/acreadiness-policy/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/github/awesome-copilot/blob/main/skills/acreadiness-policy/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

You create a configuration file (JSON) that specifies which parts to ignore and which to give more weight to. Then, you apply this rule to assess your code.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add github/awesome-copilot --skill acreadiness-policy

Or download just the file:

curl -L https://raw.githubusercontent.com/github/awesome-copilot/main/skills/acreadiness-policy/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

/acreadiness-policy — AgentRC policies

Use this skill when the user asks about policies, strict mode, custom scoring, disabling checks, org standards, or CI gating of readiness.

A policy is a small JSON file with three optional sections — criteria, extras, thresholds — that customise how AgentRC scores readiness.

Built-in examples

AgentRC ships with three example policies in examples/policies/:

Policy What it does
strict.json 100% pass rate, raises impact on key criteria
ai-only.json Disables all repo-health checks, focuses on AI tooling
repo-health-only.json Disables AI checks, focuses on traditional quality

Recommend these as starting points before writing a custom policy.

Policy schema

{
  "name": "my-policy",
  "criteria": {
    "disable":  ["env-example", "observability", "dependabot"],
    "override": {
      "readme":      { "impact": "high", "level": 2 },
      "lint-config": { "title": "Linter required" }
    }
  },
  "extras": {
    "disable": ["pre-commit"]
  },
  "thresholds": {
    "passRate": 0.9
  }
}

Impact weights

Impact Weight
critical 5
high 4
medium 3
low 2
info 0

Score = 1 − (deductions / max possible weight). Grades: A ≥ 0.9, B ≥ 0.8, C ≥ 0.7, D ≥ 0.6, F < 0.6.

Sub-commands

show

List policies currently in effect (from agentrc.config.json policies array, or none).

new <name>

Scaffold policies/<name>.json with sensible defaults. Walk the user through:

  1. What to disable — irrelevant pillars or extras for their stack (e.g. disable observability for a static site).
  2. What to raise — override impact to high or critical for must-haves (e.g. readme, codeowners).
  3. Pass-rate threshold — typical org baselines: 0.7 (lenient), 0.85 (standard), 1.0 (strict).
  4. Reference the policy from agentrc.config.json:
    { "policies": ["./policies/<name>.json"] }
    

apply <path-or-pkg>

Run agentrc readiness --json --policy <source> and re-render the report by handing off to the assess skill / ai-readiness-reporter agent. Supports chaining:

npx -y github:microsoft/agentrc readiness --json --policy ./org-baseline.json,./team-frontend.json

CI gating

Combine policies with --fail-level to enforce a minimum maturity level in CI:

- run: npx -y github:microsoft/agentrc readiness --policy ./policies/strict.json --fail-level 3

Advanced

JSON policies can disable, override, and set thresholds — but cannot add new criteria. For new detection logic, point users at AgentRC's TypeScript plugin system (docs/dev/plugins.md).

Operating rules

  • Never silently disable a pillar. If the user wants to disable observability, confirm and explain the trade-off.
  • Prefer overriding impact over disabling. Disabling hides the gap entirely; overriding lets it still appear in the report.
  • Recommend extras stay enabled. They cost nothing — they don't affect the score.
  • Suggest layering — most orgs want a baseline policy + per-team overrides chained with --policy a.json,b.json.
FAQ

What is a 'policy'?

It's a configuration file that customizes how your code quality is measured, allowing you to ignore checks or adjust their importance.

Can I create my own rules?

Yes, you can create custom policy files to meet your specific assessment needs.

What's the difference between disabling and overriding impact?

Disabling completely removes a check from the assessment. Overriding impact makes the check more important in the final score, but it still appears in the report.

Details

Original description by the author

Help the user pick, write, or apply an AgentRC policy. Policies customise readiness scoring by disabling irrelevant checks, overriding impact/level, setting pass-rate thresholds, or chaining org baselines with team overrides. Use when the user asks about strict mode, AI-only scoring, custom weights, CI gating, or wants org-wide standardisation.

repo: github/awesome-copilot

Popularity

GitHub stars
40k
Ranking position
#4980
License
MIT
Updated
10/15/2026

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