bootstrap

name	bootstrap
description	Analyze the current project and generate initial eval tasks for harness optimization. Creates regression and capability eval tasks based on project structure.
disable-model-invocation	true
allowed-tools	Read Grep Glob Bash(python3 *) Bash(git *) Bash(ls *) Write

Harness Bootstrap

Analyze this project and generate appropriate eval tasks for harness optimization.

Current project state

ls -la

Current harness surfaces

ls .claude/rules/ 2>/dev/null || echo "No rules directory"
ls .claude/skills/*/SKILL.md 2>/dev/null || echo "No project skills"
ls .claude/agents/*.md 2>/dev/null || echo "No project agents"
cat CLAUDE.md 2>/dev/null | head -50 || echo "No CLAUDE.md"

Current eval tasks

python3 ${CLAUDE_PLUGIN_ROOT}/scripts/eval_runner.py --eval-dir ${CLAUDE_PLUGIN_ROOT}/eval-tasks --cwd . 2>&1 || echo "No eval runner"

Instructions

Generate eval tasks for this project:

1. Regression tasks (eval-tasks/regression/): Easy checks that should ALWAYS pass.

   • Harness files are valid JSON/YAML
   • CLAUDE.md exists and has required sections
   • Skills have valid frontmatter
   • mh-validate passes

2. Capability tasks (eval-tasks/capability/): Harder checks measuring improvement.

   • Based on the project's actual domain and coding patterns
   • Based on recent git history (what kind of tasks are common)
   • Based on CLAUDE.md constraints (are they being followed?)

Write each task as a JSON file following the schema in eval-tasks/_schema.json. Each task must have: name, type, difficulty, description, checks (deterministic + llm_judge). Use only check types: exit_code, file_exists, file_contains, file_not_contains, json_valid, command_output.