Ocas Praxis

Bounded behavioral refinement loop. Records outcomes, extracts micro-lessons from repeated patterns, consolidates them into capped active behavior shifts, applies shifts at runtime, and generates plain-language debriefs. Use when recording outcomes, extracting lessons, managing behavior shifts, generating runtime briefs, or producing debriefs. Do not use for general memory, personality rewriting, or knowledge storage.

Praxis

Praxis improves future agent behavior through a bounded refinement loop. It records outcomes, extracts lessons from repeated patterns, consolidates them into a small active set of behavior shifts, and produces auditable debriefs.

Praxis is not a diary, general memory system, or self-rewriting identity layer. It is a bounded behavioral refinement loop.

When to use

• Record a task outcome, failure, success, or correction
• Extract lessons from repeated patterns
• Review or manage active behavior shifts
• Generate the current runtime brief (active shifts only)
• Produce a debrief explaining what changed and why

When not to use

• General knowledge storage — use Elephas
• Preference tracking — use Taste
• One-off trivia or domain facts
• Broad autobiographical summaries
• Silent personality mutation

Responsibility boundary

Praxis owns bounded behavioral refinement: events, lessons, shifts, and debriefs.

Praxis does not own: general memory (Elephas), preference persistence (Taste), pattern discovery (Corvus), communications (Dispatch), skill evaluation (Mentor).

Praxis receives BehavioralSignal files from Corvus. Praxis decides whether to act on each signal.

Commands

• praxis.event.record — record a completed event or outcome with evidence
• praxis.lesson.extract — derive micro-lessons from recorded events
• praxis.shift.propose — propose a new behavior shift from lessons
• praxis.shift.list — list all shifts with status
• praxis.shift.activate — activate a proposed shift (enforces cap)
• praxis.shift.expire — expire or reject a shift with reason
• praxis.runtime.brief — generate runtime brief with active shifts only
• praxis.debrief.generate — produce a plain-language debrief
• praxis.status — event count, active shifts, cap usage, last debrief
• praxis.journal — write journal for the current run; called at end of every run

Core loop

1. Record event → 2. Extract lessons (if pattern detected) → 3. Propose shift → 4. Activate (if cap allows) → 5. Generate debrief

Hard constraints

• No autonomous identity rewriting
• No silent safety boundary changes
• No unlimited behavior rule accumulation
• Only active shifts influence runtime
• Maximum 12 active shifts (configurable)
• Every shift must trace to recorded events

Capping and consolidation rules

Default cap: 12 active shifts. When at cap and a new shift is proposed: merge overlapping shifts, replace a weaker shift, or reject the new shift. No duplicate or contradictory active shifts.

Runtime injection rules

The runtime brief is a compact list of active shifts only. Target: 3-12 items. Imperative, behavior-facing, free of historical clutter. Not a narrative log.

Inter-skill interfaces

Praxis receives BehavioralSignal files from Corvus at: ~/openclaw/data/ocas-praxis/intake/{signal_id}.json

Praxis checks its intake directory during praxis.event.record and during any scheduled pass. Praxis decides whether to record each signal as an event and extract a lesson. It is not obligated to act on every signal.

After processing each file, move to intake/processed/.

See spec-ocas-interfaces.md for the BehavioralSignal schema and handoff contract.

Storage layout

text

~/openclaw/data/ocas-praxis/
  config.json
  events.jsonl
  lessons.jsonl
  shifts.jsonl
  debriefs.jsonl
  decisions.jsonl
  intake/
    {signal_id}.json
    processed/
  reports/

~/openclaw/journals/ocas-praxis/
  YYYY-MM-DD/
    {run_id}.json

The OCAS_ROOT environment variable overrides ~/openclaw if set.

Default config.json:

json

{
  "skill_id": "ocas-praxis",
  "skill_version": "2.0.0",
  "config_version": "1",
  "created_at": "",
  "updated_at": "",
  "shifts": {
    "max_active": 12
  },
  "lessons": {
    "min_pattern_count": 2
  },
  "retention": {
    "days": 0,
    "max_records": 10000
  }
}

OKRs

Universal OKRs from spec-ocas-journal.md apply to all runs.

yaml

skill_okrs:
  - name: shift_traceability
    metric: fraction of active shifts with at least one traced event
    direction: maximize
    target: 1.0
    evaluation_window: 30_runs
  - name: cap_compliance
    metric: fraction of runs where active shift count is at or below cap
    direction: maximize
    target: 1.0
    evaluation_window: 30_runs
  - name: lesson_precision
    metric: fraction of extracted lessons leading to activated shifts
    direction: maximize
    target: 0.50
    evaluation_window: 30_runs
  - name: debrief_quality
    metric: fraction of debriefs rated useful by human review
    direction: maximize
    target: 0.80
    evaluation_window: 30_runs

Optional skill cooperation

• Corvus — receives BehavioralSignal files via intake directory
• Dispatch — receives action decisions from Praxis for communication execution

Journal outputs

Action Journal — every event recording, lesson extraction, shift change, and debrief generation.

Visibility

public

Support file map

File | When to read references/data_model.md | Before creating events, lessons, shifts, or debriefs references/lesson_rules.md | Before extracting lessons from events references/runtime_rules.md | Before generating runtime brief references/debrief_templates.md | Before generating debriefs references/journal.md | Before praxis.journal; at end of every run