using-adaptive-harness

Adaptive-Harness Orchestration Protocol

QUICK REFERENCE — Follow this on EVERY task

This is the complete action sequence. After each step, IMMEDIATELY proceed to the next. Never pause, never respond to user mid-pipeline.

# 0. Determine mode
agent_mode = "dontAsk" if "--skip-interview" else "default"
plugin_root = Read(".adaptive-harness/.plugin-root") or "{{PLUGIN_ROOT}}"

# 1. ROUTE
router_result = Agent(subagent_type="adaptive-harness:router", mode=agent_mode, prompt="Classify: {task}\nRead .adaptive-harness/harness-pool.json")
response = parse_json(router_result)
# Router output includes ## NEXT_ACTION — follow those steps NOW, in this same response turn

# 1b. DISPLAY ROUTING SUMMARY (concise, before execution)
Output to user:
  "Routing decision:
   - Harness: {response.selected_harness or 'ensemble'}
   - Task type: {response.taxonomy.task_type} | Uncertainty: {response.taxonomy.uncertainty} | Blast radius: {response.taxonomy.blast_radius}
   - Reason: {response.reasoning}"

# 2. EXECUTE (pick ONE path)
if response.skip_routing:
    → Do the task directly. Write lightweight eval JSON. DONE.

elif response.ensemble_chains:
    → CHAIN ENSEMBLE:
    a. Ensure git repo: Bash("git rev-parse --is-inside-work-tree 2>/dev/null || (git init && git add -A && git commit --allow-empty -m init)")
    b. Run shared planning harness ONCE (no worktree)
    c. Bash("git add -A && git diff --cached --quiet || git commit -m 'planning artifacts'")
    d. Fan out sub-chains IN PARALLEL (sub_chains = [chain[1:] for chain in ensemble_chains]), each sub-chain runs sequentially in its own worktree with isolation="worktree"
    e. Read synthesizer skill: Read("{plugin_root}/harnesses/synthesizer/skill.md")
    f. Spawn synthesizer with BOTH worktree paths + skill.md → merges files into main workspace

elif response.ensemble_harnesses:
    → SIMPLE ENSEMBLE:
    a. Spawn all harnesses IN PARALLEL, each with isolation="worktree"
    b. Spawn synthesizer with worktree paths + skill.md

elif response.harness_chain and len > 1:
    → CHAIN: Write .chain-in-progress marker, execute sequentially, remove marker when done

else:
    → SINGLE: Read agent.md + skill.md, spawn one harness subagent

# 3. EVALUATE (immediately after execution completes)
Agent(subagent_type="adaptive-harness:evaluator", mode=agent_mode, prompt="Score result...")

# 4. RECORD (write eval JSON, update weights, copy to evaluation-logs/)

# 5. REPORT to user