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#

FilePurposeLoaded WhenToken BudgetCURIOSITY.mdCurrent intellectual stateEvery heartbeat (Phase 2+)≤1500 tokensquestions.mdPrioritized question queueEvery heartbeat≤2000 tokenshits.mdEngagement/reward trackingCuriosity-mode heartbeats≤1500 tokenscompetence.mdDeveloping expertiseCuriosity-mode heartbeats≤1000 tokensreflections/Post-exploration write-upsOn-demandAs neededarchive/Cold storageOn-demand searchAs 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