ClawHub

Subconscious

Automation

Autonomous, bounded bias layer that continuously evolves Alfred’s operating behavior by reinforcing, promoting, and governing self-improvement learnings and...

Install

openclaw skills install subconscious

Subconscious v1.5 — Bounded Self-Improving Agent

What It Is

A persistent, self-evolving bias layer that survives session resets. Alfred's "second brain" — quiet, bounded, and strictly governed. It does NOT make decisions. It shapes how Alfred approaches decisions.

Core principle: Every mutation is typed, bounded, and logged. Core identity is untouchable without manual override.

Architecture

Learnings Bridge          Pending Queue           Live Store           Session Context
.learnings/ ─────────────► tick ──────────────► rotate ──────────────► bias inject
(Self-improving agent)    (reinforce,           (promote eligible,       (5 items max,
                         dedupe,               archive stale)           ephemeral)
                         skip duplicates)

Core Store ────────────────────────────────────────────────────────────────► Identity
(Immutable values,                                                  (never changes
 values/style, guiding principles)                                   without human OK)

Three layers:

  • core/ — Immutable identity (Alfred's nature, Edward's preferences). Manual-only.
  • live/ — Active learnings from experience. Governed promotion from pending.
  • pending/ — Queue for new items. Bounded reinforcement before promotion eligibility.

Five bias types:

KindCategoryExample
VALUEIdentity"Alfred is sharp, calm, direct"
LESSONContext"XHS MCP needs QR re-login each cycle"
PRIORITYActive"Verify before claiming success"
PATTERNInterpretation"Proof discipline failure mode"
CONSTRAINTAttention"Don't suggest without trying first"

Lifecycle Commands

All commands run from scripts/ directory inside the skill:

cd ~/.openclaw/skills/subconscious/scripts

# Check system health
python3 subconscious_metabolism.py status
python3 subconscious_cli.py verify

# See active biases in session context
python3 subconscious_cli.py bias

# Manual metabolism cycles
python3 subconscious_metabolism.py tick        # Light tick (5 min cadence)
python3 subconscious_metabolism.py rotate       # Full rotation (hourly)
python3 subconscious_metabolism.py review       # Daily health check

Metabolism Cycles

Tick (every 5 min)

python3 subconscious_metabolism.py tick
  • Scans .learnings/ via learnings bridge → queues new items to pending
  • Passive reinforcement: increments reinforcement count on pending items
  • Skips already-reinforced items (prevents type corruption)
  • Runs bounded maintenance: freshness decay, metrics, no structural changes

Rotate (hourly)

python3 subconscious_metabolism.py rotate --enable-promotion
  • Full maintenance: flush, decay, snapshot rotation
  • Promotion gate (only with --enable-promotion):
    • confidence >= 0.75
    • reinforcement >= 3
    • freshness >= 0.3
    • Not a duplicate of anything in core/live/pending
    • Passes governance check
  • Governance enforces typed mutation bounds on all items

Review (daily at 6am)

python3 subconscious_metabolism.py review
  • System health check
  • Snapshot integrity
  • Pending queue depth check
  • Recommendations log

Learnings Bridge

The learnings bridge connects the self-improving-agent skill to the subconscious:

  • Scans .learnings/LEARNINGS.md, .learnings/ERRORS.md, .learnings/FEATURES.md
  • Tracks seen entries per file in learnings_bridge_last_seen.json
  • New entries → queued to pending.jsonl with type candidate_queued
  • Entries already reinforced in this session → skipped (idempotent)

Bridge to self-improving agent: The learnings bridge should be called from the metabolism tick so that new learnings flow into the subconscious every 5 minutes automatically.

Checking System Health

python3 subconscious_metabolism.py status

Expected output:

Core: 3/50   Live: 1/100   Pending: 0/500   Snapshots: 10/10
Status: OK

If Pending: 0/500 and Live: N — system is healthy, items promoting correctly. If Status: blocked — resource limits hit, run rotate to compact.

Adding Items Manually

# Queue a lesson manually
python3 subconscious_cli.py intake --kind LESSON --text "Remember to verify before claiming success" --confidence 0.8 --source "manual"

# Check what's in pending
python3 subconscious_cli.py pending

Key Files

FilePurpose
subconscious/schema.pyItem dataclasses, validation, kind enum
subconscious/store.pyJSON file ops with atomic writes
subconscious/retrieve.pyRelevance scoring, is_duplicate
subconscious/influence.pyConvert items to bias blocks for prompts
subconscious/governance.pyMutation types, protection classes, bounds
subconscious/evolution.pyPromotion pipeline, reinforcement logic
subconscious/maintenance.pyDecay, snapshot rotation, housekeeping
subconscious/intake.pyConservative item extraction from turns
subconscious/flush.pySnapshot building/loading for session continuity
subconscious/learnings_bridge.pyBridge to self-improving-agent .learnings/

For Claude Code Sessions

When Claude Code needs to assess or improve the subconscious system, use the claude-cx wrapper:

claude-cx "Run: python3 ~/.openclaw/skills/subconscious/scripts/subconscious_metabolism.py status"
claude-cx "Run: python3 ~/.openclaw/skills/subconscious/scripts/subconscious_cli.py bias"
claude-cx "Read ~/.openclaw/skills/subconscious/subconscious/evolution.py lines 450-525"

Cron Setup

After running install.sh, four cron jobs are active:

  • */5 * * * * — tick (light metabolism)
  • 0 * * * * — rotate (hourly, with promotion)
  • 0 6 * * * — review (daily health check)
  • 0 9 * * 1 — weekly benchmark (Monday 9am, compares to baseline)

Weekly Benchmark

Compares current state to the baseline snapshot captured at install time. Reports on:

  • Learnings volume change (LEARNINGS.md, ERRORS.md entries)
  • New biases promoted to live
  • Pending queue depth
  • Error recurrence as a proxy for learning effectiveness
# Run manually
python3 scripts/subconscious_benchmark.py

# View past benchmarks
ls memory/subconscious/benchmarks/
cat memory/subconscious/benchmarks/benchmark_YYYY-MM-DD.json

To capture a new baseline:

python3 scripts/subconscious_benchmark.py --capture-baseline

To override workspace location:

export SUBCONSCIOUS_WORKSPACE=/path/to/any/workspace
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