Caliber

Hand-written CLAUDE.md files go stale the moment you refactor. Your AI agent hallucinates paths that no longer exist, misses new dependencies, and gives advice based on yesterday's architecture. Caliber generates and maintains your AI context files (CLAUDE.md, .cursor/rules/, AGENTS.md, copilot-instructions.md) so they stay accurate as your code evolves — and keeps every agent on your team in sync, whether they use Claude Code, Cursor, Codex, OpenCode, or GitHub Copilot.

Before / After

Most repos start with a hand-written CLAUDE.md and nothing else. Here's what Caliber finds — and fixes:

  Before                                    After /setup-caliber
  ──────────────────────────────            ──────────────────────────────

  Agent Config Score    35 / 100            Agent Config Score    94 / 100
  Grade D                                   Grade A

  FILES & SETUP           6 / 25            FILES & SETUP          24 / 25
  QUALITY                12 / 25            QUALITY                22 / 25
  GROUNDING               7 / 20            GROUNDING              19 / 20
  ACCURACY                5 / 15            ACCURACY               13 / 15
  FRESHNESS               5 / 10            FRESHNESS              10 / 10
  BONUS                   0 / 5             BONUS                   5 / 5

Scoring is deterministic — no LLM, no API calls. It cross-references your config files against your actual project filesystem: do referenced paths exist? Are code blocks present? Is there config drift since your last commit?

caliber score --compare main    # See how your branch changed the score

Get Started

Requires Node.js >= 20.

npx @rely-ai/caliber bootstrap

Then, in your terminal (not the IDE chat), start a Claude Code or Cursor CLI session and type:

/setup-caliber

Your agent detects your stack, generates tailored configs for every platform your team uses, sets up pre-commit hooks, and enables continuous sync — all from inside your normal workflow.

Don't use Claude Code or Cursor? Run caliber init instead — it's the same setup as a CLI wizard. Works with any LLM provider: bring your own Anthropic, OpenAI, MiniMax, or Vertex AI key.

Your code stays on your machine. Bootstrap is 100% local — no LLM calls, no code sent anywhere. Generation uses your own AI subscription or API key. Caliber never sees your code.

Audits first, writes second

Caliber never overwrites your existing configs without asking. The workflow mirrors code review:

1. Score — read-only audit of your current setup
2. Propose — generate or improve configs, shown as a diff
3. Review — accept, refine via chat, or decline each change
4. Backup — originals saved to .caliber/backups/ before every write
5. Undo — caliber undo restores everything to its previous state

If your existing config scores 95+, Caliber skips full regeneration and applies targeted fixes to the specific checks that are failing.

How It Works

Bootstrap gives your agent the /setup-caliber skill. Your agent analyzes your project — languages, frameworks, dependencies, architecture — generates configs, and installs hooks. From there, it's a loop:

  npx @rely-ai/caliber bootstrap       ← one-time, 2 seconds
              │
              ▼
  agent runs /setup-caliber             ← agent handles everything
              │
              ▼
  ┌──── configs generated ◄────────────┐
  │           │                        │
  │           ▼                        │
  │     your code evolves              │
  │     (new deps, renamed files,      │
  │      changed architecture)         │
  │           │                        │
  │           ▼                        │
  └──► caliber refresh ──────────────►─┘
       (auto, on every commit)

Pre-commit hooks run the refresh loop automatically. New team members get nudged to bootstrap on their first session.

What It Generates

Claude Code

• CLAUDE.md — Project context, build/test commands, architecture, conventions
• CALIBER_LEARNINGS.md — Patterns learned from your AI coding sessions
• .claude/skills/*/SKILL.md — Reusable skills (OpenSkills format)
• .mcp.json — Auto-discovered MCP server configurations
• .claude/settings.json — Permissions and hooks

Cursor

• .cursor/rules/*.mdc — Modern rules with frontmatter (description, globs, alwaysApply)
• .cursor/skills/*/SKILL.md — Skills for Cursor
• .cursor/mcp.json — MCP server configurations

OpenAI Codex

• AGENTS.md — Project context for Codex
• .agents/skills/*/SKILL.md — Skills for Codex

OpenCode

• AGENTS.md — Project context (shared with Codex when both are targeted)
• .opencode/skills/*/SKILL.md — Skills for OpenCode

GitHub Copilot

• .github/copilot-instructions.md — Project context for Copilot

Key Features

caliber init --agent claude        # Claude Code only
caliber init --agent cursor        # Cursor only
caliber init --agent codex         # Codex only
caliber init --agent opencode        # OpenCode only
caliber init --agent github-copilot  # GitHub Copilot only
caliber init --agent all             # All platforms
caliber init --agent claude,cursor   # Comma-separated

caliber learn install      # Install hooks for Claude Code and Cursor
caliber learn status       # View hook status, event count, and ROI summary
caliber learn finalize     # Manually trigger analysis (auto-runs on session end)
caliber learn remove       # Remove hooks

caliber hooks --install    # Enable refresh hooks
caliber hooks --remove     # Disable refresh hooks

git config caliber.autostage false

Commands

FAQ

LLM Providers

No API key? No problem. Caliber works with your existing AI tool subscription:

Override the model for any provider: export CALIBER_MODEL=<model-name> or use caliber config.

Caliber uses a two-tier model system — lightweight tasks (classification, scoring) auto-use a faster model, while heavy tasks (generation, refinement) use the default. This keeps costs low and speed high.

Configuration is stored in ~/.caliber/config.json with restricted permissions (0600). API keys are never written to project files.

MiniMax supports OpenAI-compatible and Anthropic-compatible requests in both service regions. Set MINIMAX_BASE_URL or choose a base URL with caliber config:

# Custom region
export VERTEX_PROJECT_ID=my-gcp-project
export VERTEX_REGION=europe-west1

# Service account credentials (inline JSON)
export VERTEX_PROJECT_ID=my-gcp-project
export VERTEX_SA_CREDENTIALS='{"type":"service_account",...}'

# Service account credentials (file path)
export VERTEX_PROJECT_ID=my-gcp-project
export GOOGLE_APPLICATION_CREDENTIALS=/path/to/service-account.json

Contributing

See CONTRIBUTING.md for detailed guidelines.

git clone https://github.com/caliber-ai-org/ai-setup.git
cd caliber
npm install
npm run dev      # Watch mode
npm run test     # Run tests
npm run build    # Compile

Uses conventional commits — feat: for features, fix: for bug fixes.

Add a Caliber badge to your repo

After scoring your project, add a badge to your README:

Copy this markdown and replace 94 with your actual score:

![Caliber Score](https://img.shields.io/badge/caliber-SCORE%2F100-COLOR)

Color guide: brightgreen (90+), green (70-89), yellow (40-69), red (<40).

License

MIT