arc-observing

name	arc-observing
description	Use when user asks about behavioral patterns, requests instinct status, or wants to confirm/contradict a detected pattern

Behavioral Observation & Instinct Management

Overview

Manage automatically detected behavioral patterns (instincts) from tool usage observations. The observer daemon runs in the background as an orchestrator: it captures tool-call observations, assembles batches, calls the LLM curator to generate candidate proposals, and ingests those proposals into the learning queue. Confirmed instincts are loaded as behavioral guidance at session start.

Three layers in arcforge — this skill handles Behavioral:

• Behavioral (instincts) — auto-detected from tool usage patterns (this skill). Focuses on tool-usage workflow patterns only. User preferences and project context are handled by Claude Code's native auto-memory.
• Continuity (sessions) — user-controlled save/resume for session handoff
• Learning (diary→reflect→learn) — deliberate reflection for pattern extraction

Quick Reference

Task	Command
View instincts	node "${SKILL_ROOT}/scripts/instinct.js" status --project {p}
Confirm pattern	node "${SKILL_ROOT}/scripts/instinct.js" confirm {id} --project {p}
Contradict pattern	node "${SKILL_ROOT}/scripts/instinct.js" contradict {id} --project {p}
Daemon status	bash "${SKILL_ROOT}/scripts/observer-daemon.sh" status
Start daemon	bash "${SKILL_ROOT}/scripts/observer-daemon.sh" start
Stop daemon	bash "${SKILL_ROOT}/scripts/observer-daemon.sh" stop

Infrastructure Commands

Set SKILL_ROOT from skill loader header (# SKILL_ROOT: ...):

: "${SKILL_ROOT:=${ARCFORGE_ROOT:-}/skills/arc-observing}"
if [ ! -d "$SKILL_ROOT" ]; then
  echo "ERROR: SKILL_ROOT=$SKILL_ROOT does not exist. Set ARCFORGE_ROOT or SKILL_ROOT manually." >&2
  exit 1
fi

How Observations Work

The observer daemon is a four-layer orchestrator:

1. Capture: hooks/observe/main.js records every tool call to ~/.arcforge/observations/{project}/observations.jsonl
2. Batch assembly (Layer 3): Daemon calls node $CURATOR_CLI assemble-batch --project to gather recent observation windows into a structured batch
3. LLM curation (Layer 4): Daemon invokes claude --model haiku --max-turns 15 --print --output-format json --json-schema with the batch. The LLM curator produces structured candidate proposals rather than direct instinct file writes
4. Ingestion (Layer 5): Daemon calls node $CURATOR_CLI ingest-proposal --batch-id --response-file to parse the LLM response and append candidates to the review queue at ~/.arcforge/learning/candidates/queue.jsonl

The daemon never writes instinct .md files directly, and SessionStart never auto-loads instinct bodies by confidence. All candidate proposals flow through the LLM curator into the review queue; human review via arcforge learn dashboard is the only path that produces active instinct files (Layer 8 activation). Dashboard-activated instincts are injected at SessionStart, but only through that explicit activation gate — the top 5 by confidence, with confidence used to sort and cap rather than as a threshold, and an inject_activated_instincts kill-switch (default ON).

Instinct Format

---
id: grep-before-edit
trigger: "when modifying code in a file"
confidence: 0.65
domain: workflow
source: session-observation
project: my-api
last_confirmed: 2026-02-08
confirmations: 8
contradictions: 0
---

# Grep Before Edit

## Action
Always use Grep to find the exact location before using Edit.

## Evidence
- Observed 8 times in session abc123 (2026-02-08)
- Pattern: Grep → Read → Edit sequence

Storage

~/.arcforge/
├── observations/{project}/
│   ├── observations.jsonl          # Current (append-only)
│   └── archive/                    # Processed observations
│
├── instincts/
│   ├── {project}/
│   │   ├── grep-before-edit.md     # Atomic instincts
│   │   └── archived/               # Decayed instincts
│   ├── global/                     # Cross-project (promoted via dashboard)
│   ├── global-index.jsonl          # Bubble-up tracking
│   ├── config.json                 # Observer configuration
│   └── .observer.pid               # Daemon PID file
│
└── learning/
    ├── candidates/
    │   └── queue.jsonl             # LLM curator output (pending review)
    └── dashboard/
        └── actions.jsonl           # Dashboard action audit log

Confidence Lifecycle

Confidence is metadata stored on the candidate / activated instinct record. It does not drive runtime auto-loading. It informs which records to surface in dashboard / arc-recalling / history views.

Auto-detected by daemon: confidence 0.5
Confirmed → +0.05 (cap 0.9)
Contradicted → -0.10 (floor 0.1), -0.05 for manual/reflection sources
No activity → -0.02/week, -0.01/week for manual/reflection sources

>= 0.7 → Surfaced prominently in dashboard / arc-recalling
0.3-0.7 → Listed as summary
< 0.3 → Silent
< 0.15 → Archived (moved to archived/ subdir)

Daemon Safety

• Re-entrancy guard: The daemon checks for a .analyzing.lock file with a 30-minute stale TTL before running the LLM curator. Concurrent daemon runs are blocked automatically.
• Watchdog: A OBSERVER_DAEMON_WATCHDOG_SECS (default 120s) timeout prevents hung LLM curator calls from blocking subsequent runs.
• Skip filter: ARCFORGE_OBSERVE_SKIP_PATHS and .eval-trials/ paths are excluded from observation capture to prevent eval noise from polluting the learning queue.

When to Use

• User asks "what patterns have you noticed?"
• User wants to see instinct status dashboard
• User confirms or contradicts a detected pattern
• User asks about behavioral observation system
• Presenting instincts loaded at session start

When NOT to Use

• User wants to combine related instincts into a higher-level candidate (use the dashboard Evolve action: arcforge learn dashboard)
• User wants to capture session reflections (use arc-journaling)
• User wants to analyze diary entries (use arc-reflecting)

Process

Presenting Instincts

When showing instincts to users, group by domain and show confidence bars:

## WORKFLOW (3)

  ████████░░  80%  grep-before-edit
            trigger: when modifying code
            action: Always grep first

  ██████░░░░  60%  read-before-write
            trigger: when creating files
            action: Check if file exists first

Confirming/Contradicting

When user agrees or disagrees with a pattern:

1. Run confirm/contradict CLI command
2. Show updated confidence
3. Explain the change

Bubble-up to Global

Patterns appearing in 2+ projects can be promoted to ~/.arcforge/instincts/global/ via the dashboard Promote action. The Promote action requires explicit user authorization — silent auto-promotion is not supported.

Common Mistakes

Confusing Instincts with Learned Skills

Wrong: Manually creating instincts for techniques Right: Instincts are auto-detected from behavior; combine them via the dashboard Evolve action (arcforge learn dashboard)

Ignoring Low-Confidence Instincts

Wrong: Treating all instincts equally Right: Surface >= 0.7 prominently in dashboard / arc-recalling; summaries for 0.3-0.7; hide < 0.3. Confidence informs surfacing, not runtime auto-loading.

Not Updating Confidence

Wrong: Showing instincts without offering confirm/contradict Right: Always offer user the chance to validate or reject patterns