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Acreadiness Policy skill

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.

$npx skills add github/awesome-copilot --skill acreadiness-policy
GitHub stars
41,017
Pack installs
2.4M
Alyn Score
80/99
Updated
20 h ago
License
MIT

GitHub

Acreadiness Policy

Install Acreadiness Policy

Pick your agent. Every command is ready to paste.

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

The open skills CLI detects your agents (Claude Code, Cursor, Codex and 70+ more) and installs to the right folder. Add -g to install globally.

01

Install it

Run the command above, or upload the folder in Claude.

02

Ask naturally

Describe the task. Your agent loads acreadiness-policy when the request matches its description.

03

Name it if needed

If it does not trigger, say “use the acreadiness-policy skill”. In Codex, type $acreadiness-policy.

The skill itself

SKILL.md

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.

Tips for Acreadiness Policy

  • • Start a fresh session after installing so your agent picks up the new skill.
  • • It is part of a pack with 40 skills. Install only the ones you need with --skill to keep triggers precise.
  • • If two skills overlap, mention the one you want by name.

Questions about Acreadiness Policy

What does the Acreadiness Policy skill do?

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.

How do I install Acreadiness Policy?

Run "npx skills add github/awesome-copilot --skill acreadiness-policy" in your project. The skills CLI installs it for Claude Code, Cursor, Codex and 70+ other agents. In Claude on the web, upload the skill folder as a ZIP under Customize > Skills.

Does Acreadiness Policy work in Cursor and Codex?

Yes. Acreadiness Policy uses the open SKILL.md format, so it works in Claude Code, Claude, Cursor, OpenAI Codex, Gemini CLI, GitHub Copilot and other agents that support agent skills.

Is Acreadiness Policy free?

Acreadiness Policy is open source on GitHub under the MIT license. It is free to install; check the license before commercial use.

Who made Acreadiness Policy?

Acreadiness Policy is published by GitHub in the github/awesome-copilot repository, together with 39 other skills.

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