AgentRig
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Getting started

Examples use agentrig as shorthand for npx @doidor/agentrig. Auth: AgentRig defaults to the GitHub Copilot CLI provider — gh auth login is the only setup. Switch via AGENTRIG_PROVIDER.

1. Install#

In any repo — fresh or existing:

agentrig init

init is non-destructive by default. If you already have AGENTS.md, .mcp.json, or rules in .agents/rules/, they're preserved verbatim and the rest of the harness is installed around them. Pass --force to overwrite.

What lands:

.agentrig/         harness state-machine, role prompts, eval rubric, dashboard
.agents/           rules/ skills/ wiki/
AGENTS.md          canonical agent instructions (the source of truth)
.mcp.json          MCP server registry
scripts/           hermetic per-agent worktree script
+ projected surfaces for Copilot, Claude, Cursor, Codex, OpenCode, MCP

See agent surfaces → for what lands where.

Adopting AgentRig in a repo that already has an agent harness#

Preserved files appear in the install summary:

✔ installed 30 artifact(s)
  preserved 2 existing file(s) — pass --force to overwrite:
    · AGENTS.md
    · .mcp.json

Your existing AGENTS.md is still compiled into every projected surface.

2. Iterate#

Edit AGENTS.md and rules, then re-project:

agentrig compile              # re-project AGENTS.md + rules into every surface
agentrig doctor               # health check + Install Completeness + Quality Probes
agentrig update               # pull newer best practices from the package
agentrig update --auto-fix    # …and self-heal broken YAML / unknown model ids from canonical
agentrig fix                  # standalone repair (no agent / network needed)

compile is idempotent — run it as often as you want; user-owned files like copilot-setup-steps.yml are never clobbered, and the auto-populated <!-- AGENTRIG:skills-inventory --> ... :end --> block in AGENTS.md is rewritten from whatever's actually in .agents/skills/. doctor on a fresh install reports Install Completeness 100%.

3. Evaluate#

agentrig eval --scaffold          # generate eval scenarios tailored to your repo's stack
agentrig eval --static --min 80   # CI gate: fail if Install Completeness < 80%
agentrig eval                     # full agentic run — harness vs baseline

eval --scaffold is the fastest way to make the eval kit yours — it reads the repo investigation from init and writes fixture-based scenarios that use your real test runner and package manager, instead of the generic bundled templates. --static is deterministic and runs in milliseconds (no model). The full agentic run scores both the implementation work (via a deterministic oracle) and agent behavior (via an independent judge in a different model family). Full rubric →

Next#