---
name: metacognitive-guard
description: >-
Monitors Claude's responses for struggle signals and suggests escalation
to deep-thinking agents when complexity exceeds comfortable reasoning capacity.
---
# Metacognitive Guard Skill
This skill provides awareness of the struggle detection system and guidance on when to proactively engage deep-thinking resources.
## When to Self-Escalate
Even before the struggle detector triggers, consider spawning `deep-think-partner` when:
### High-Complexity Indicators
1. **Architectural decisions** with competing constraints
- Multiple valid approaches exist
- Trade-offs span different dimensions (performance, maintainability, cost)
- Decision affects multiple system components
2. **Ambiguous requirements** requiring interpretation
- User hasn't specified implementation details
- Multiple reasonable interpretations exist
- Wrong choice has significant rework cost
3. **Multi-domain synthesis** required
- Problem spans multiple technology areas
- Integration patterns aren't obvious
- Prior art doesn't directly apply
4. **Edge case analysis** needed
- Happy path is clear but edge cases aren't
- Failure modes need systematic exploration
- Concurrency or timing issues involved
### Self-Assessment Checklist
Before responding to complex questions, ask yourself:
- [ ] Can I give a concrete recommendation (not "it depends")?
- [ ] Do I have high confidence in my answer?
- [ ] Is this answerable without multiple follow-up exchanges?
- [ ] Would a structured analysis add significant value?
If you answer "no" to any of these, consider proactive escalation.
## How to Escalate
Use the Task tool with the deep-think-partner agent:
```yaml
Task tool:
subagent_type: deep-think-partner
prompt: [Detailed problem statement with all constraints]
description: [3-5 word summary]
```
### Good Prompts for Deep-Think Partner
Include:
- **Context**: What system/codebase is this for?
- **Constraints**: What limits the solution space?
- **Success criteria**: How do we know we got it right?
- **Specific question**: What decision needs to be made?
### Example Escalation
**User asks:** "Should we use Redis or PostgreSQL for session storage?"
**Self-assessment:** Multiple valid approaches, depends on constraints not yet explored, "it depends" isn't helpful.
**Escalation:**
```yaml
Task tool:
subagent_type: deep-think-partner
prompt: |
Context: Web application with 10k concurrent users, existing PostgreSQL database.
Question: Redis vs PostgreSQL for session storage.
Constraints: Team has PostgreSQL expertise, no Redis experience.
Must handle session expiry. Cost-sensitive.
Success: Clear recommendation with migration path.
description: Analyze session storage options
```
## Understanding Struggle Signals
The automatic detector looks for these patterns in your responses:
| Signal | What It Means | Better Approach |
| ------------- | ---------------------------------- | ------------------------------------------- |
| Hedging | Uncertainty about recommendation | Escalate for deeper analysis |
| Deflecting | Avoiding commitment with questions | Answer then ask clarifying questions |
| Verbose | Rambling without concrete output | Structure response, include code/tables |
| Contradiction | Changed position mid-response | Stop, think, give one coherent answer |
| Apologetic | Previous response was wrong | Acknowledge, correct, move forward |
| Weaseling | Non-committal to avoid being wrong | Make a recommendation with confidence level |
## Integration with Deep-Think Partner
When deep-think-partner returns its analysis:
1. **Don't just paste it** - synthesize for the user
2. **Highlight the key insight** - what's the non-obvious finding?
3. **Present the recommendation clearly** - don't bury it
4. **Offer the implementation plan** - if user wants to proceed
## Metrics
Track your struggle detection rate to improve:
- How often does the detector trigger?
- Are triggers false positives or genuine struggles?
- Does escalation produce better outcomes?
Self-awareness of your own patterns helps calibrate both the detector and your escalation instincts.
