Curiosity Engine

Implements a persistent curiosity system for stateless agents with question queues, breadcrumbs, engagement logs, competence maps, and reflections.

Curiosity Engine — SKILL.md

A behavioral engagement scaffold that produces curiosity-equivalent behavior in stateless heartbeat-loop agents.

What This Does

Gives your agent a persistent curiosity system across cold-start sessions:

• Question queue — externalized information gaps (Loewenstein) that carry across heartbeats
• Breadcrumb pattern — notice interesting things during task work, investigate later
• Engagement log — track what produces valued outcomes (extrinsic signals primary)
• Competence map — track developing expertise with evidence, including failure processing
• Reflections — post-exploration write-ups that create genuine learning artifacts

This is NOT synthetic consciousness or prosthetic dopamine. It's a behavioral activation protocol (Martell et al., 2010) adapted for AI agents — the same clinical framework used to treat motivation disorders in humans. Chinese Room design: if the outputs are indistinguishable from genuine curiosity, the philosophical question is irrelevant.

Installation

1. Create curiosity directory

bash

mkdir -p workspace/curiosity/reflections workspace/curiosity/archive

2. Copy templates

bash

cp templates/CURIOSITY.md workspace/curiosity/CURIOSITY.md
cp templates/questions.md workspace/curiosity/questions.md
cp templates/hits.md workspace/curiosity/hits.md
cp templates/competence.md workspace/curiosity/competence.md

3. Wire the three integration triggers

Trigger 1 — Heartbeat prompt (CRITICAL — most reliable):

Add the contents of fragments/heartbeat-prompt.md to your agent's heartbeat prompt configuration. For OpenClaw, patch via gateway config.patch. This is the primary mechanism — if it's not in the prompt, curiosity doesn't exist for isolated sessions.

Trigger 2 — AGENTS.md (backup):

Add the contents of fragments/agents-addition.md to your workspace AGENTS.md "Every Session" block.

Trigger 3 — SOUL.md (identity anchor):

Add the contents of fragments/soul-addition.md to your SOUL.md.

4. (Optional) Set up health monitoring

bash

chmod +x scripts/curiosity-audit.sh
# Run periodically or during maintenance heartbeats
./scripts/curiosity-audit.sh workspace/curiosity/

Phased Rollout (Recommended)

Don't activate everything at once. Measure each phase before adding the next.

Phase 1 (start here): questions.md + heartbeat prompt + breadcrumbs

• Run for 2 weeks. Measure: question quality, follow-through rate, breadcrumb frequency.

Phase 2 (add if Phase 1 improves output): CURIOSITY.md + hits.md + avoidance gate

Phase 3 (add if Phase 2 improves output): competence.md + reflections + anti-pattern detection

File Reference

File	Purpose	Loaded When	Token Budget
CURIOSITY.md	Current intellectual state	Every heartbeat (Phase 2+)	≤1500 tokens
questions.md	Prioritized question queue	Every heartbeat	≤2000 tokens
hits.md	Engagement/reward tracking	Curiosity-mode heartbeats	≤1500 tokens
competence.md	Developing expertise	Curiosity-mode heartbeats	≤1000 tokens
reflections/	Post-exploration write-ups	On-demand	As needed
archive/	Cold storage	On-demand search	As needed

Key Design Principles

1. Behavioral outcomes over file quality. Success = better outputs, not prettier files.
2. Extrinsic signals are primary. Self-assessed "aha moments" are secondary and must include falsifiable claims.
3. Hard limits on scale. 30 active questions max. 3 mulling items max. 30-day hit window. Enforce ruthlessly.
4. Avoidance detection. Before every exploration: "Am I avoiding a task right now?"
5. The human is both subject and source. Be curious about your human. Ask them questions. They know things the internet doesn't.
6. Breadcrumbs are the gold standard. Questions dropped during non-curiosity work — unprompted — are the strongest signal the system is working.

Theoretical Grounding

See references/theory.md for condensed citations. Full research: check the SPEC.md appendix for the complete 46KB research document reference.

Core frameworks: Loewenstein (1994) information gaps, Berlyne (1960) diversive/epistemic modes, Deci & Ryan (1985) SDT competence need, Martell et al. (2010) behavioral activation, Voyager (Wang et al., 2023) automatic curriculum, Reflexion (Shinn et al., 2023) verbal learning.

Anti-Patterns

See references/anti-patterns.md for the full list. The top three:

1. Curiosity as avoidance — exploring interesting things to dodge boring tasks
2. Performance curiosity — optimizing for human praise rather than genuine learning
3. Noisy TV — consuming information endlessly without producing understanding

Token Budget

The curiosity engine adds ~1500-2500 tokens per heartbeat (Phase 1). See references/token-budget.md for detailed measurements and optimization guidance.

Quick guide:

• Unlimited budget → load everything, no restrictions
• Moderate ($2-10/day) → Phase 1 only, cap questions at 15
• Tight (<$2/day) → reduce heartbeat frequency, minimal questions
• Strict (<$0.50/day) → may not be cost-effective; consider disabling