| name | setup |
| description | Use when a repository needs AI Harness setup, repair/update, AGENTS.md refresh, AI memory refresh, vocabulary cleanup, or review after major codebase changes |
Set Up AI Harness
Overview
Use this skill for first setup and later refreshes. The published CLI owns deterministic structure; this skill owns semantic repository understanding.
Humans and agents use the same deterministic entrypoint. Do not reimplement init, doctor, path repair, symlink repair, or managed file repair inside this skill. Call the CLI through npx.
Bootstrap / Update Harness
Before inspecting repository meaning, announce the deterministic setup steps you are about to run.
From the repository root, run:
npx --yes @blazity-atlas/ai-harness@latest doctor
Then follow the CLI result:
- If AI Harness is missing or mostly uninitialized, run
npx --yes @blazity-atlas/ai-harness@latest init.
- If
doctor reports only fixable drift, run npx --yes @blazity-atlas/ai-harness@latest doctor --fix.
- If
doctor --fix refuses because of a dirty worktree, stop and ask the user whether to commit, stash, or explicitly rerun with --force. Do not use --force automatically.
- If
doctor reports manual conflicts, summarize those conflicts and stop before semantic setup.
- Rerun
npx --yes @blazity-atlas/ai-harness@latest doctor after any init or fix command.
- Continue only when
doctor exits clean.
If the current directory is not a git repository, stop and ask the user to run the skill from the repository root or initialize git first.
Required Grounding
- After the deterministic bootstrap is clean, read
.ai/config.json and resolve every artifact location through it.
- Inspect the repository before asking questions: README, package metadata, lockfiles, framework configs, existing docs, tests, and agent instructions.
- Infer only obvious facts from code. Ask about product, domain, ownership, and workflow details that code cannot answer.
- Mark unknowns explicitly instead of inventing facts.
Customization Gate
After deterministic setup is clean and the repository has been inspected, ask whether the user wants standard setup or repository-specific AI Harness customization.
- If the user chooses standard setup, continue with the normal initial setup or refresh flow below.
- If the user chooses customization, or if their prompt already explicitly asks to customize AI Harness, read
customization.md from this setup skill directory and follow that workflow.
- Do not read
customization.md for a standard setup or refresh.
Modes
Initial Setup
Use when the harness is new or mostly empty. Build the first useful AI context for the repository.
Refresh
Use after major codebase, architecture, dependency, command, or product changes. Compare existing AI context with the current repository and update only stale or missing facts.
Interview Rules
- Ask one focused question at a time.
- Do not ask questions that repository inspection can answer.
- Recommend a default answer when asking the user to choose.
- Keep questions focused on facts that affect future agent behavior.
Good questions cover: product purpose, target users, current direction, deploy/runtime expectations, architectural invariants, common pitfalls, safe commands, branch/release workflow, domain vocabulary, and external systems.
Outputs
- Keep
AGENTS.md concise and high-signal. Preserve human content and the AI Harness managed block.
- Fill
.ai/LANGUAGE.md with canonical terms and avoided synonyms.
- Fill
.ai/memory/product.md, .ai/memory/architecture.md, and .ai/memory/stack.md with stable facts only.
- Append
.ai/memory/lessons.md only for proven non-obvious pitfalls.
- Do not create new artifact roots. Use
.ai/config.json paths.
- Run
npx --yes @blazity-atlas/ai-harness@latest doctor again before reporting completion.
Quality Bar
AGENTS.md should help an agent work safely within the first minute: what this repo is, how it is structured, what commands are safe, what rules matter, and what not to touch. Prefer short factual sections over long prose.
