/acreadiness-policy — AgentRC policies
SkillDev toolsHelps your agent pick, write, or apply an AgentRC policy that customises readiness scoring with custom checks, weights, and thresholds.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the /acreadiness-policy — AgentRC policies skill
About this capability
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,
What this skill tells your AI
The instructions your AI receives, as published by github/awesome-copilot in skills/acreadiness-policy/SKILL.md and read by ahel’s review.
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:
- What to disable — irrelevant pillars or extras for their stack (e.g. disable
observabilityfor a static site). - What to raise — override
impacttohighorcriticalfor 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 <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
impactover 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.
Signals
- GitHub stars
- 39k
- Forks
- 5k
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
acreadiness-policy- Source
- github.com/github/awesome-copilot