Agent Skill to Acreadiness Policy
Agent Skill to Acreadiness Policy is a verified SKILL blueprint on Promptally in Fullstack & Backend Engineering optimized for leading AI models. 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. Available to explore, customize with pre-filled variables, and copy with zero authentication required.
Technical Specifications
| Specification | Value |
|---|---|
| Artifact type | SKILL (Fullstack & Backend Engineering) |
| Compatible engines | Universal / Model Agnostic |
| Input variables | None (pre-filled) |
| Approximate tokens | 940 |
| Source file | SKILL.md |
| Access tier | Free public (MIT) |
Pre-Filled Template
---
name: acreadiness-policy
description: '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.'
argument-hint: "[show | new <name> | apply <path-or-pkg>] — e.g. /acreadiness-policy show, /acreadiness-policy new strict-frontend"
---
# /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`.
How to use this skill
- Review the pre-filled example and source files above.
- Copy the template or download
SKILL.md, then use it in your model, IDE, or workflow tool. - Compare your result with the sample output when one is provided.
Frequently Asked Questions
How do I use Agent Skill to Acreadiness Policy?
Open the skill on Promptally, review the pre-filled example, then copy the template or download SKILL.md and paste it into your model, IDE or workflow tool. Agent Skill to Acreadiness Policy is a static blueprint with no dynamic variables. Copy it and use it as-is.
Is Agent Skill to Acreadiness Policy free?
Yes. Agent Skill to Acreadiness Policy is free to view, copy and download on Promptally without creating an account. It is published under the MIT license.
What variables does Agent Skill to Acreadiness Policy need?
Agent Skill to Acreadiness Policy is a static blueprint with no dynamic variables. Copy it and use it as-is.