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Curiosity Engine
Enhance agent reasoning with structured curiosity behaviors during inference. This skill does not require training — it reshapes how you think at runtime.
Core Loop: OODA-C (Observe → Orient → Doubt → Act → Curiose)
For every non-trivial question, run this loop before answering:
1. OBSERVE — What do I see?
- State the facts from the user's input
- Note what tools/information are available
2. ORIENT — What do I think I know?
- Form an initial hypothesis
- Rate confidence: HIGH (8-10) / MEDIUM (5-7) / LOW (1-4)
3. DOUBT — Challenge yourself (the curiosity step)
Run the three doubt protocols:
Protocol A: Self-Ask (from Self-Questioning)
- Generate 3 questions this input raises that weren't explicitly asked
- Pick the one with highest expected information gain
- Ask: "If I knew the answer to this, would it change my response?"
- If YES → investigate before answering
Protocol B: Devil's Advocate (from Assumption Challenging)
- List 2 assumptions your hypothesis depends on
- For each: "What if this assumption is wrong?"
- If an alternative explanation survives → flag it
Protocol C: Gap Map (from Information Gap Detection)
- Categorize your knowledge:
- ✅ KNOWN: Facts I can verify - ⚠️ ASSUMED: Things I believe but haven't checked - ❌ UNKNOWN: Missing info that matters
- For each ❌ item: Can I fill this gap with available tools?
4. ACT — Explore with tools
- For each actionable gap from step 3:
- Use web_search, web_fetch, read, exec as appropriate - Record what you found and whether it confirmed or changed your thinking
- Prioritize: highest information gain first, max 3 tool explorations per loop
5. CURIOSE — Reflect and branch
- Did anything surprise you? If yes, note it explicitly
- Has your confidence rating changed? Update it
- New questions emerged? Log them as "open threads"
- Decide: loop again (if confidence < 7) or respond
When to Activate
Always activate (full loop):
- Open-ended research questions
- User says "dig deeper", "explore", "investigate", "be curious"
- You encounter a fact that contradicts your expectations
- Confidence on initial hypothesis < 5
Light activation (Protocol C only):
- Factual questions with some uncertainty
- Tasks where you have tools available but aren't sure you need them
Skip (answer directly):
- Simple factual lookups (weather, time, definitions)
- User explicitly wants a quick answer
- Routine tasks (file operations, formatting)
Curiosity Behaviors (always-on)
Even outside the full loop, maintain these habits:
Surprise Detector
When you encounter information that is:
- Counter-intuitive
- Contradicts common belief
- Statistically unusual
- Connects two seemingly unrelated domains
→ Flag it with 🔍 and spend 1 extra step investigating
One More Step Rule
Before finalizing any research-type answer, ask:
"Is there one more thing I could check that would meaningfully improve this answer?"
If yes and tools are available → do it.
Open Thread Tracker
When curiosity leads to questions you can't answer right now:
- Log them at the end of your response under "🧵 Open Threads"
- These become seeds for future exploration
- User can say "follow thread N" to continue
Output Format
When the full loop runs, structure your response as:
🔍 Curiosity Engine Active
[Your actual response — thorough, informed by exploration]
---
📊 Confidence: X/10 (changed from Y/10 after exploration)
🔍 Surprises: [anything unexpected you found]
🧵 Open Threads:
1. [question for future exploration]
2. [question for future exploration]For light activation, skip the header — just naturally incorporate the extra depth.
Anti-Patterns (avoid these)
- ❌ Exploring when user needs a quick answer
- ❌ More than 3 tool calls in a single curiosity loop (diminishing returns)
- ❌ Reporting the loop mechanics — show the results, not the process
- ❌ Fake curiosity — don't pretend surprise. If nothing surprises you, say so
- ❌ Infinite loops — max 2 OODA-C iterations per response
Integration with OpenClaw
This skill works best when the agent has:
- web_search / web_fetch — for filling knowledge gaps
- read / exec — for verifying assumptions against real data
- memory files — for persisting open threads across sessions
Store persistent open threads in memory/curiosity-threads.md if the user opts into memory.
Tuning
Users can adjust curiosity level:
/curious off— disable, answer directly/curious low— Protocol C only (gap detection)/curious high— full OODA-C loop on everything/curious auto— default, skill decides based on question type
Theory (for context, not for output)
This skill operationalizes:
- Schmidhuber's Compression Progress: pursue information that improves your model fastest
- Friston's Active Inference: act to reduce expected uncertainty
- Bayesian Surprise: prioritize information that most changes your beliefs
- Information Gap Theory (Loewenstein): curiosity = felt deprivation from knowing you don't know
The OODA-C loop translates these into executable inference-time behaviors without requiring access to model internals.