Acreadiness Policy
GitHubOfficialFirst committed by mvanderbend-msoftDistributed by GitHub
- Skill
- Workflow
- Software development
- MIT
- Low risk
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
The acreadiness-policy skill enables users to define, manage, and apply custom policies that dictate how AgentRC evaluates project readiness. By creating JSON-based policy files, users can tailor scoring by disabling specific checks, overriding impact levels for criteria, and setting required pass-rate thresholds. This skill supports organizational standardization by allowing teams to chain baseline policies with team-specific overrides, making it ideal for enforcing quality standards in CI/CD pipelines.
What it does
- Scaffolds new readiness policy files with sensible defaults.
- Allows disabling of specific readiness checks or extra features.
- Supports overriding impact weights and levels for specific criteria.
- Defines pass-rate thresholds for automated scoring.
- Facilitates chaining multiple policies for layered organizational requirements.
- Integrates with CI workflows to enforce maturity levels via gating.
When to use it
- When you need to standardize readiness scoring across an organization.
- When you want to enforce strict quality gates in CI/CD pipelines.
- When specific readiness checks are irrelevant to your project stack.
- When you need to prioritize certain criteria by increasing their impact weight.
- When you want to transition from default scoring to a custom, team-specific baseline.
Advantages
- Provides granular control over how project maturity is measured.
- Supports layered policy application for flexible team-level overrides.
- Enables automated enforcement of quality standards in CI environments.
- Reduces noise by allowing the exclusion of irrelevant checks.
Usage examples
- “/acreadiness-policy new strict-frontend”
- The agent scaffolds a new policy file named strict-frontend.json, prompting the user to define specific criteria, impact overrides, and pass-rate thresholds.
- “/acreadiness-policy apply ./policies/org-baseline.json,./policies/team-frontend.json”
- The agent executes the readiness assessment using the chained policy files, applying the organizational baseline followed by the team-specific overrides.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/github/acreadiness-policy/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip acreadiness-policy.zip -d .agents/skills
Documentation by mvanderbend-msoft
/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:
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.jsonCI 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 3Advanced
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.
Files
- ATTRIBUTION.mdAdded by AutoGineer887 B
- LICENSELicence file added by AutoGineer1.0 KiB
- SKILL.md3.7 KiB
Requirements and compatibility
Written for: GitHub Copilot, Claude Code
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Claude Code frontmatter, Needs Node.js
Security
What our scanner noticed· Low risk
- Instructions that use the network
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- First committed by
mvanderbend-msoft
- Publisher
- GitHub (Official)
- Distributed by
- GitHub
- Source
- github/awesome-copilot · skills/acreadiness-policy · commit 797337f
- Licence
- MIT License (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
- Contributors
- mvanderbend-msoft
AutoGineer is not affiliated with or endorsed by mvanderbend-msoft or GitHub.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download acreadiness-policy.zip