General

acreadiness-policy - Claude MCP 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.

SEO Guide: Enhance your AI agent with the acreadiness-policy tool. This Model Context Protocol (MCP) server allows Claude Desktop and other LLMs to help the user pick, write, or apply an agentrc policy. policies customise readiness scoring by disab... Download and configure this skill to unlock new capabilities for your AI workflow.

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SKILL.md
# /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

```jsonc
{
  "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`:
   ```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:
```bash
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:

```yaml
- 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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Information

Repository
github/awesome-copilot
Author
github
Last Sync
9/5/2026
Repo Updated
9/5/2026
Created
5/4/2026

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