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Forge the Anvil — PI Orchestrator Fix

Plan: Forge the Anvil — PI Orchestrator Fix

Research Summary

Analysed pi-orchestrator.js (1706 lines), ollama-tool-agent.js (548 lines), hivemind.js (994 lines), dag-scheduler.js (394 lines), plus MC stats, minions.db, events.db, and HiveMind data.

Key findings:

  • Minion runs: 24 total, 5 completed (21%), 16 cancelled, 3 failed
  • Event chain: 62 delegates → 11 completions (18%)
  • Proof-of-work bug CONFIRMED: reportCompletion() line 1091 checks for GOTCHA/verify dir BEFORE line 1104 creates them
  • Budget flat $2.00 for all Claude CLI tasks (line 782)
  • ollama-tool-agent: MAX_TURNS=10, no JSON repair, no retry
  • HiveMind: 6,843 entries, only 4 types have TTLs — briefing/alert/coordination. Everything else permanent
  • dag-scheduler already has fail() — no work needed
  • routing-outcomes.db exists but tracks routing, not task outcomes

Objective

Fix the 3 highest-impact bugs in PI orchestrator, harden the ollama agent, and add basic outcome tracking. Target: minion completion >50% on next 20+ runs.

Team Orchestration

Team Members

ID Name Role Agent Type
B1 proof-of-work-builder Fix reportCompletion ordering + budget scaling builder
V1 proof-of-work-validator Validate proof-of-work fix + budget validator
B2 ollama-hardening-builder Harden ollama-tool-agent builder
V2 ollama-hardening-validator Validate ollama hardening validator
B3 hivemind-ttl-builder Add TTLs + outcome tracking builder
V3 hivemind-ttl-validator Validate HiveMind + tracking validator

Step-by-Step Tasks

Phase 1: Fix Proof-of-Work Bug + Budget Scaling (HIGHEST IMPACT)

Task 1: Fix reportCompletion proof-of-work ordering

  • Owner: B1
  • BlockedBy: none
  • File: ~/system/kernel/pi-orchestrator.js
  • What: Move the "AUTO QA PREP" block (lines 1104-1146) BEFORE the "VALIDATION GATE" check (lines 1079-1101). The auto-prep creates /tmp/verify-{id} and /tmp/gotcha-task-{id}.md that the gate checks for. Currently gate checks first → always fails for local models that can't write these files.
  • Acceptance:
    • Auto-prep block executes BEFORE proof-of-work check
    • Proof-of-work check still blocks if auto-prep produced nothing AND agent produced nothing
    • node -c ~/system/kernel/pi-orchestrator.js passes (syntax valid)

Task 2: Scale Claude CLI budget by complexity

  • Owner: B1
  • BlockedBy: 1
  • File: ~/system/kernel/pi-orchestrator.js (pipelineClaudeCLI function, line 782)
  • What: Replace hardcoded '--max-budget-usd', '2.00' with complexity-based budget. Read complexity from task or modelSelection. Map: complexity 1-2=$0.50, 3=$1.00, 4=$2.00, 5=$5.00.
  • How: The pipelineClaudeCLI function already receives task parameter. Add budget lookup before spawn. Pass task.budget or compute from modelSelection.tier.
  • Acceptance:
    • Budget varies by tier (check spawn args in code)
    • Tier 5 gets $5.00, Tier 4 gets $2.00, lower tiers get less
    • Syntax check passes

Task 3: Add human-active backoff

  • Owner: B1
  • BlockedBy: 2
  • File: ~/system/kernel/pi-orchestrator.js (runCycle function, around line 1234)
  • What: At top of runCycle, check if /tmp/mc-active-task exists and is fresh (<5 min). If so, skip Claude CLI tasks (set claude concurrency to 0 for this cycle). Local models still run.
  • Acceptance:
    • When human is active, cloud tasks are deferred
    • Local model tasks still execute
    • When marker is stale (>5 min), normal behavior resumes

Task 4: Validate Phase 1 fixes

  • Owner: V1
  • BlockedBy: 3
  • What: Read pi-orchestrator.js and verify all 3 changes. Run syntax check. Verify auto-prep is before gate check. Verify budget is dynamic. Verify human backoff logic.
  • Acceptance:
    • node -c ~/system/kernel/pi-orchestrator.js exits 0
    • Auto-prep block appears BEFORE proof-of-work check in reportCompletion
    • Budget in pipelineClaudeCLI is NOT hardcoded $2.00
    • runCycle has human-active check

Phase 2: Harden Ollama Tool Agent

Task 5: Increase MAX_TURNS and add JSON repair

  • Owner: B2
  • BlockedBy: none (parallel with Phase 1)
  • File: ~/system/tools/ollama-tool-agent.js
  • What:
    1. Change MAX_TURNS = 10 to MAX_TURNS = 20 (line 44)
    2. In the JSON parse block (around line 320), add fallback: if JSON.parse(jsonStr) fails, try regex extraction /{[\s\S]*}/ and retry parse
    3. In tool execution (around line 338-352), wrap in retry: if TOOLS[tool].exec throws, retry once with 2s delay
  • Acceptance:
    • MAX_TURNS is 20
    • JSON parse has regex fallback before giving up
    • Tool execution retries once on failure
    • node -c ~/system/tools/ollama-tool-agent.js passes

Task 6: Validate ollama-tool-agent changes

  • Owner: V2
  • BlockedBy: 5
  • What: Read ollama-tool-agent.js. Verify MAX_TURNS, JSON repair, and retry logic.
  • Acceptance:
    • MAX_TURNS = 20
    • JSON fallback regex exists after parse failure
    • Tool exec has try/catch with retry
    • Syntax valid

Phase 3: HiveMind TTL + Outcome Tracking

Task 7: Add aggressive TTLs to HiveMind

  • Owner: B3
  • BlockedBy: none (parallel with Phase 1 and 2)
  • File: ~/system/agents/hivemind/hivemind.js (TTL_DAYS object, line 201)
  • What: Expand TTL_DAYS to cover high-volume types currently permanent: 
    briefing: 3       (was 7)
alert: 14          (was 30)
coordination_request: 7  (unchanged)
coordination_response: 7 (unchanged)
update: 7          (NEW — 306 entries)
info: 7            (NEW — 378 entries)
queue: 3           (NEW — 302 entries)
error: 14          (NEW — 290 entries)
report: 14         (NEW — 284 entries)
task-update: 7     (NEW — 221 entries)
task: 7            (NEW — 116 entries)
spam: 1            (NEW — 99 entries)
intake: 7          (NEW — 94 entries)
  • Acceptance:
    • TTL_DAYS has 13+ entries (was 4)
    • briefing reduced to 3 days
    • alert reduced to 14 days
    • spam has 1 day TTL
    • Syntax valid

Task 8: Add task outcome tracking to pi-orchestrator

  • Owner: B3
  • BlockedBy: 7
  • File: ~/system/kernel/pi-orchestrator.js
  • What: After verifyQuality in runCycle (around line 1293), record outcome to ~/system/databases/learning-loop.db:
    1. Create SQLite DB + table at top of file (lazy init like other DBs): 
      CREATE TABLE IF NOT EXISTS task_outcomes (
  id INTEGER PRIMARY KEY AUTOINCREMENT,
  mc_task_id INTEGER, task_domain TEXT, task_type TEXT,
  complexity INTEGER, tier INTEGER, model TEXT, pipeline TEXT,
  success BOOLEAN, quality_score REAL, response_length INTEGER,
  latency_ms INTEGER, failure_reason TEXT, priority TEXT,
  created_at TEXT DEFAULT (datetime('now'))
);
    2. Insert row after quality gate check (both pass and fail paths)
    3. Also insert on pipeline failure (result.success=false path)
  • Acceptance:
    • learning-loop.db gets created on first run
    • task_outcomes table has correct schema
    • Outcomes recorded for success AND failure paths
    • Syntax valid

Task 9: Selective HiveMind feedback

  • Owner: B3
  • BlockedBy: 8
  • File: ~/system/kernel/pi-orchestrator.js (feedbackToHiveMind function, line 1211)
  • What: Currently stores ALL tier 2+ responses >200 chars. Change to:
    1. Only store tier 3+ responses (skip tier 2 — too much noise)
    2. Truncate to 1000 chars (was 5000)
    3. Skip if quality gate failed (no failed responses into HiveMind)
  • Acceptance:
    • feedbackToHiveMind checks tier >= 3 (was >= 2)
    • Truncation is 1000 chars (was 5000)
    • Function is only called after quality gate passes

Task 10: Validate Phase 3

  • Owner: V3
  • BlockedBy: 9
  • What: Read hivemind.js and pi-orchestrator.js. Verify TTLs, outcome tracking, and selective feedback.
  • Acceptance:
    • HiveMind TTL_DAYS has 13+ entries
    • learning-loop.db schema is correct
    • feedbackToHiveMind only stores tier 3+, truncated to 1000 chars
    • Both files pass syntax check

Validation Commands

# Syntax check all modified files
node -c ~/system/kernel/pi-orchestrator.js
node -c ~/system/tools/ollama-tool-agent.js
node -c ~/system/agents/hivemind/hivemind.js

# Restart daemon
launchctl kickstart -k gui/501/com.john.pi-orchestrator

# Monitor
tail -f ~/system/logs/pi-orchestrator.log

# Check HiveMind cleanup
node ~/system/agents/hivemind/hivemind.js cleanup

# Check learning loop DB
sqlite3 ~/system/databases/learning-loop.db "SELECT COUNT(*) FROM task_outcomes"

What This Plan Does NOT Include (Intentionally)

  • Workflow engine — premature. Fix the basics first.
  • Adaptive router (Thompson Sampling) — only 24 data points. Need 100+ outcomes before routing optimization makes sense.
  • Project coordinator — can't orchestrate projects if single tasks fail.
  • Daemon consolidation — works fine, not broken.
  • Contract test suite — nice to have but not the bottleneck.

These belong in Phase 2 AFTER Gate 1 metrics prove the foundation works.

Gate 1 Success Criteria

After these fixes, run PI orchestrator for 48h and measure:

  • Minion Success Rate > 50% on 20+ new tasks
  • No false completions (tasks marked done with no output)
  • HiveMind entry count drops after cleanup
  • learning-loop.db has outcome data for every task attempt
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