acreadiness-policy skill

by github·github/awesome-copilot·39k stars·MIT

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.

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Install the acreadiness-policy skill

A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description.

git clone --depth 1 https://github.com/github/awesome-copilot.git /tmp/awesome-copilot
mkdir -p ~/.claude/skills
cp -r /tmp/awesome-copilot/skills/acreadiness-policy ~/.claude/skills/acreadiness-policy

available in every project

In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub

The instructions your agent would load

SKILL.md as published, without the frontmatter. Read it on 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/:

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

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

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

What to disable — irrelevant pillars or extras for their stack (e.g. disable observability for a static site).
What to raise — override impact to high or critical for must-haves (e.g. readme, codeowners).
Pass-rate threshold — typical org baselines: 0.7 (lenient), 0.85 (standard), 1.0 (strict).
Reference the policy from agentrc.config.json:

{ "policies": ["./policies/<name>.json"] }

apply

Run agentrc readiness --json --policy 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.

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