Monitor Taxonomy

Taxonomy quality monitor that assesses correctness of bridge_attributes and collection_tags on memory documents via a three-tier cascade.

Key distinction from monitor-memory: monitor-memory checks coverage/method/drift. monitor-taxonomy checks correctness via cascade validation.

Continuous Operation (Non-Negotiable)

This skill is always-on. It:

• Runs on its configured schedule indefinitely — it NEVER stops unless explicitly halted by the user
• The agent MUST NOT stop and wait for the human to ask for status or remember to check
• If a cycle fails, diagnose the failure, attempt auto-repair, and continue
• Only escalate to the human if genuinely blocked after exhausting /dogpile research
• Gracefully handles restarts and maintains state across cycles
• Is designed for multi-day/week/month autonomous operation

Anti-pattern: Reporting status and waiting for the human to ask "what next?" is UNACCEPTABLE. The agent must proactively fix issues and continue the monitoring loop.

Architecture

Document with bridge_attributes
         │
    ┌────▼────┐
    │  Tier 0  │  Heuristic: vocabulary validation, null check,
    │ (instant) │  text-bridge coherence (keyword overlap score)
    └────┬────┘
         │ confidence < 0.80
    ┌────▼─────┐
    │ Tier 1.5  │  Trained classifier (after 50+ labels)
    │ (~200ms)  │  OR small GPT (after /create-gpt training)
    └────┬─────┘
         │ confidence < 0.85 ("maybe" zone)
    ┌────▼────┐
    │  Tier 2  │  Brandon (scillm persona) — authoritative teacher
    │ (~3s)    │  Full semantic assessment → training_labels.jsonl
    └────┬────┘
         │
    Grade: CORRECT / MISTAGGED / MISSING / HALLUCINATED
    Action: keep / re-extract / remove / flag

Commands

# Run all probes
./run.sh check --json

# Run a specific tier
./run.sh check --tier 0 --autofix --json

# Run a single probe
./run.sh check --probe null-bridge-gc --json

# Dashboard
./run.sh dashboard

# Status (labels, shadow, classifier)
./run.sh status

# Register nightly schedule
./run.sh register-nightly

# Help
./run.sh help

Probes

Tier 0 — Heuristic Quality (instant, deterministic)

Tier 1.5 — Classifier/GPT Quality (after training)

Tier 2 — Brandon Teacher + Training

Nightly Schedule

03:00  monitor-taxonomy T0: Heuristic quality (P01-P05) + auto-fix
03:15  monitor-taxonomy T1.5: Classifier quality (P10-P12) — skips if no model
03:30  monitor-taxonomy T2: Brandon teacher (P20-P23) — validates flagged docs

Runs BEFORE monitor-memory at 05:00. Taxonomy fixes applied before coverage measured.

Environment Variables