autoresearch-wrapper-run

name	autoresearch-wrapper-run
description	Start or resume a dependency-aware autoresearch-wrapper run in Git worktrees. Use when the target and metric are already configured and the user wants to initialize or continue the optimization loop.

Autoresearch Wrapper Run

Use the launcher next to this skill:

if [ -n "${CLAUDE_SKILL_DIR:-}" ]; then
  AUTORESEARCH_RUNNER="${CLAUDE_SKILL_DIR}/run.sh"
elif [ -n "${CLAUDE_PLUGIN_ROOT:-}" ]; then
  AUTORESEARCH_RUNNER="${CLAUDE_PLUGIN_ROOT}/skills/autoresearch-wrapper-run/run.sh"
elif [ -f ".claude/skills/autoresearch-wrapper-run/run.sh" ]; then
  AUTORESEARCH_RUNNER="$(readlink -f ".claude/skills/autoresearch-wrapper-run/run.sh")"
elif [ -f "skills/autoresearch-wrapper-run/run.sh" ]; then
  AUTORESEARCH_RUNNER="$(readlink -f "skills/autoresearch-wrapper-run/run.sh")"
else
  echo "Could not resolve the autoresearch-wrapper-run launcher" >&2; exit 1
fi

Use:

bash "$AUTORESEARCH_RUNNER" run

When this skill is invoked:

1. Start or resume the current run.
2. If the run is blocked, explain whether the missing requirement is:

• target selection
• metric configuration
• execution settings
• dependency-aware readiness

3. If the run starts successfully, summarize:

• run id
• target part
• generated program.md
• seed worktree
• any preallocated candidates
• execution mode (sequential, parallel, or wild)

4. Remind the user that the underlying loop uses:

• allocate
• evaluate
• record

5. If early exit is configured, inform the user:

• patience setting (how many rounds without improvement before stopping)
• threshold setting (minimum improvement to count as progress)
• the run will end with status early_exit if the patience is exceeded

6. If wild mode is configured, inform the user:

• wild mode performs simultaneous multi-parameter changes
• wild_max_simultaneous controls how many parameters change at once
• the search widens automatically when improvement stalls

Example

• /autoresearch-wrapper-run