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2 changes: 1 addition & 1 deletion .github/prompts/generate-improvements.prompt.md
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Expand Up @@ -48,7 +48,7 @@ You are a senior software engineer reviewing the **AgentRC** project — a TypeS
- Safe file writes: only overwrites with `--force` flag (`safeWriteFile` in `src/utils/fs.ts`)
- Copilot SDK integration via `@github/copilot-sdk` with session-based agent conversations
- GitHub token resolution: `GITHUB_TOKEN` → `GH_TOKEN` → `gh auth token` fallback chain
- Readiness uses a leveled criteria system (levels 1-5) across 9 pillars with pass/fail/skip status
- Readiness uses a leveled criteria system (levels 1-5) across 10 pillars with pass/fail/skip status
- Build with `tsup`, test with `vitest`, lint with `eslint`, format with `prettier`

## Your Task
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1 change: 1 addition & 0 deletions CHANGELOG.md
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Expand Up @@ -6,6 +6,7 @@ All notable changes to this project will be documented in this file.

### Features

- **Workflow automation readiness pillar** — add scored checks for issue templates, PR templates, commit conventions, PR auto-labeling, and release automation; readiness now reports across 10 pillars.
- **`--dry-run` for generate** — preview which files would be created or skipped without writing anything (`agentrc generate mcp --dry-run`)
- **JSONC support** — `agentrc.config.json`, `agentrc.eval.json`, and policy files now accept `//` and `/* */` comments
- **Array eval expectations** — `expectation` field in eval configs accepts `string[]` for structured criteria
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28 changes: 15 additions & 13 deletions README.md
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Expand Up @@ -26,7 +26,7 @@ Works as a CLI, as a [VS Code extension](docs/extension.md), and in your [CI/CD

### Measure

Score your repo’s AI-readiness across 9 pillars and a 5-level maturity model. Find out what context is missing — from basic linting to MCP server configs.
Score your repo’s AI-readiness across 10 pillars and a 5-level maturity model. Find out what context is missing — from basic linting and workflow automation to MCP server configs.

```bash
npx github:microsoft/agentrc readiness
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## Documentation

| | |
| ---------------------------------------------- | ------------------------------------------------------- |
| **[Getting Started](docs/getting-started.md)** | Prerequisites and first run |
| **[Concepts](docs/concepts.md)** | Maturity model, readiness pillars, how generation works |
| **[Commands](docs/commands.md)** | Full CLI reference |
| **[Configuration](docs/configuration.md)** | Areas, workspaces, monorepos |
| **[Policies](docs/policies.md)** | Custom readiness scoring |
| **[At Scale](docs/at-scale.md)** | Batch processing across orgs |
| **[CI Integration](docs/ci-integration.md)** | GitHub Actions & Azure Pipelines |
| **[VS Code Extension](docs/extension.md)** | Sidebar views, commands, settings |
| **[Agent Plugin](plugin/README.md)** | Install as a Copilot agent plugin with built-in skills |
| **[Examples](examples/)** | Configs, evals, and policies |
| | |
| -------------------------------------------------------- | ------------------------------------------------------- |
| **[Getting Started](docs/getting-started.md)** | Prerequisites and first run |
| **[Concepts](docs/concepts.md)** | Maturity model, readiness pillars, how generation works |
| **[Commands](docs/commands.md)** | Full CLI reference |
| **[Configuration](docs/configuration.md)** | Areas, workspaces, monorepos |
| **[Policies](docs/policies.md)** | Custom readiness scoring |
| **[At Scale](docs/at-scale.md)** | Batch processing across orgs |
| **[CI Integration](docs/ci-integration.md)** | GitHub Actions & Azure Pipelines |
| **[VS Code Extension](docs/extension.md)** | Sidebar views, commands, settings |
| **[Maturity Models](docs/maturity-models.md)** | Canonical readiness levels, checks, and rollout signals |
| **[Maturity in Practice](docs/maturity-in-practice.md)** | How those levels feel in day-to-day adoption |
| **[Agent Plugin](plugin/README.md)** | Install as a Copilot agent plugin with built-in skills |
| **[Examples](examples/)** | Configs, evals, and policies |

[Customize AI in VS Code](https://code.visualstudio.com/docs/copilot/customization/overview) · [Custom instructions](https://code.visualstudio.com/docs/copilot/customization/custom-instructions) · [CONTRIBUTING.md](CONTRIBUTING.md)

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2 changes: 1 addition & 1 deletion docs/commands.md
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Expand Up @@ -57,7 +57,7 @@ agentrc analyze [path]

## `agentrc readiness`

Score readiness across 9 pillars. See [Concepts — Readiness pillars](concepts.md#readiness-pillars).
Score readiness across 10 pillars. See [Concepts — Readiness pillars](concepts.md#readiness-pillars) and [Maturity Models](maturity-models.md).

```bash
agentrc readiness [path]
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23 changes: 12 additions & 11 deletions docs/concepts.md
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Expand Up @@ -30,22 +30,23 @@ agentrc readiness --fail-level 3

## Readiness pillars

The readiness score is based on 9 pillars, grouped into two categories:
The readiness score is based on 10 pillars, grouped into two categories:

### Repo Health

These pillars measure general engineering maturity — things that benefit any development workflow, not just AI:

| Pillar | What it checks |
| ------------------- | ----------------------------------------------------------------------------- |
| **Style** | Linter config (ESLint/Biome/Prettier), type-checking config (TypeScript/Mypy) |
| **Build** | Build script in package.json, CI workflow config |
| **Testing** | Test script in package.json, area-scoped test scripts |
| **Docs** | README, CONTRIBUTING guide, area-scoped READMEs |
| **Dev Environment** | Lockfile (npm/pnpm/yarn/bun), `.env.example` |
| **Code Quality** | Formatter config (Prettier/Biome) |
| **Observability** | Observability dependencies (OpenTelemetry, Pino, Winston, Bunyan) |
| **Security** | LICENSE, CODEOWNERS, SECURITY.md, Dependabot config |
| Pillar | What it checks |
| ----------------------- | --------------------------------------------------------------------------------------- |
| **Style** | Linter config (ESLint/Biome/Prettier), type-checking config (TypeScript/Mypy) |
| **Build** | Build script in package.json, CI workflow config |
| **Testing** | Test script in package.json, area-scoped test scripts |
| **Docs** | README, CONTRIBUTING guide, area-scoped READMEs |
| **Dev Environment** | Lockfile (npm/pnpm/yarn/bun), `.env.example` |
| **Code Quality** | Formatter config (Prettier/Biome) |
| **Observability** | Observability dependencies (OpenTelemetry, Pino, Winston, Bunyan) |
| **Security** | LICENSE, CODEOWNERS, SECURITY.md, Dependabot config, branch protection |
| **Workflow Automation** | Issue templates, PR templates, commit conventions, PR auto-labeling, release automation |

### AI Setup

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4 changes: 2 additions & 2 deletions docs/dev/product.md
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Expand Up @@ -16,7 +16,7 @@ This gap widens at scale. An organization with hundreds of repos can't manually

AgentRC automates the preparation work that makes AI coding agents effective:

1. **Assess** — Score any repo against a 9-pillar readiness model spanning repo health (style, build, testing, docs, dev environment, code quality, observability, security) and AI setup (instructions, MCP, agents, skills). Get a maturity level from 1–5.
1. **Assess** — Score any repo against a 10-pillar readiness model spanning repo health (style, build, testing, docs, dev environment, code quality, observability, security, workflow automation) and AI setup (instructions, MCP, agents, skills). Get a maturity level from 1–5.

2. **Generate** — Use the Copilot SDK to analyze a repo and produce tailored `copilot-instructions.md` or `AGENTS.md` files. Monorepo-aware: generates per-area instructions scoped with `applyTo` globs.

Expand Down Expand Up @@ -50,7 +50,7 @@ Organizations can define **readiness policies** to customize which criteria are
## Key Design Decisions

- **Instructions are generated, not templated.** AgentRC uses the Copilot SDK to analyze actual repo content — no generic boilerplate.
- **Readiness is measurable.** The 9-pillar model produces a numeric score and maturity level, making it possible to set org-wide baselines and CI gates.
- **Readiness is measurable.** The 10-pillar model produces a numeric score and maturity level, making it possible to set org-wide baselines and CI gates.
- **Evaluation closes the loop.** Teams can prove that instructions actually improve AI output, with configurable pass-rate thresholds.
- **Policy-driven compliance.** Policies are composable JSON files that can be checked into repos or distributed org-wide.
- **Batch-first.** Every workflow that works on one repo also works on hundreds — same CLI, same output format.
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