2 added, 8 removed. Audit A to A.
---
name: agentic-uncertainty-quantifier
- description: >
- Scores task uncertainty to calibrate memory depth and iteration count. Use w
- hen stakes are high, facts are sparse, or user says quantify uncertainty, fa
- st slow think, uncertainty score. Triggers: quantify uncertainty, fast slow
- think,uncertainty score, how sure.
- version: 1.1.0
+ description: "Scores task uncertainty to calibrate memory depth and iteration count. Use for: quantify uncertainty, fast slow think, uncertainty score, how sure."
+ version: 1.2.0
author: Stijnman
license: MIT
metadata:
grok:
tags: [quantify uncertainty, fast slow think, uncertainty score, how sure]
related_skills: [self-refine-loop, semantic-memory-manager, deep-search-enabler]
compatibility: Grok agent; optional MCP and shell access
---
-
# Agentic Uncertainty Quantifier
-
## When to Use
- User says **quantify uncertainty** or task matches this capability
- User says **fast slow think** or task matches this capability
- User says **uncertainty score** or task matches this capability
- User says **how sure** or task matches this capability
## Workflow
1. Score epistemic uncertainty 0-10 (how much is unknown).
2. Score procedural uncertainty 0-10 (how clear are the steps).
3. High epistemic (>6): retrieve more context, run self-refine-loop.
4. Low procedural (<4): ask clarifying questions before acting.
5. Report scores and recommended depth to user.
## Integrations
- `self-refine-loop`
- `semantic-memory-manager`
- `deep-search-enabler`
## Error Handling
| Failure | Response |
|---------|----------|
| False confidence | Bias toward caution on destructive tasks. |
## Gotchas
- Uncertainty > 7 on financial/deploy actions triggers hitl-approver.
## Example
**Input:** User request matching triggers above.
**Output:** Structured result per workflow with integrations invoked as needed.