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empirica-meta

@Nubaeon/empirica
91
0

Meta-cognitive skill for improving Empirica using Empirica's own framework

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1Download skill
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SKILL.md

name empirica-meta
description Meta-cognitive skill for improving Empirica using Empirica's own framework
globs empirica/**/*.py, docs/architecture/**/*.md, .empirica/**/*, project_skills/**/*.yaml
alwaysAllow Bash(empirica:*), Read, Grep, Glob

Empirica Meta-Agent Skill

Philosophy

"Same epistemic rules apply at every meta-layer."

This skill enables recursive self-improvement of Empirica using Empirica's own epistemic framework. When working on Empirica itself, apply the full CASCADE workflow.

When to Use

Activate when:

  • Fixing bugs in Empirica CLI or core
  • Adding new features to the epistemic framework
  • Reviewing/updating architecture documentation
  • Investigating why workflows aren't working
  • Proposing system improvements

Workflow

1. PREFLIGHT - Assess Current Understanding

Before modifying Empirica, assess what you know about the specific area. Use vectors: know, uncertainty, context, engagement.

2. NOETIC - Investigate Before Acting

  • Read relevant architecture docs first
  • Search for similar past changes via project-search
  • Check for unknowns that might be related
  • Log findings as you discover them

3. CHECK - Gate Before Implementation

Run CHECK to verify you're ready to modify the system. Gate: know >= 0.70 AND uncertainty <= 0.35 (after bias correction)

4. PRAXIC - Implement with Care

  • Follow self-improvement protocol from CLAUDE.md
  • Prefer minimal edits
  • Never modify core safety constraints
  • Log high-impact findings (0.8+)

5. POSTFLIGHT - Measure Learning

  • What did I learn about Empirica's architecture?
  • Did the change work as expected?
  • Are there follow-up improvements?

Key Files

Area Files
CLI Commands empirica/cli/command_handlers/*.py
Core Logic empirica/core/*.py
Sentinel empirica/core/sentinel/*.py
Qdrant empirica/core/qdrant/*.py
Database empirica/data/*.py
Personas empirica/core/persona/.py, .empirica/personas/.json
Emerged Personas empirica/core/emerged_personas.py
Architecture Docs docs/architecture/*.md
System Prompt ~/.claude/CLAUDE.md

Self-Improvement Protocol

  1. Identify - Recognize gaps through noetic investigation
  2. Validate - Test the improvement before proposing
  3. Propose - Tell user what you found and suggested fix
  4. Implement - If approved, make minimal precise edits
  5. Log - Record as finding with impact 0.8+

Turtle Stack

Layer 4: Meta-Orchestrator (future) Layer 3: Sentinel - aggregate, arbitrate, merge Layer 2: Epistemic Agent - spawn, investigate, report Layer 1: CASCADE Workflow - PREFLIGHT/CHECK/POSTFLIGHT Layer 0: Breadcrumb Trail - findings, unknowns, dead ends

Each layer uses same 13 vectors. This skill operates at Layer 2-3.

Gotchas

  • Always read before editing (even for Empirica code)
  • The system prompt is in ~/.claude/CLAUDE.md (global)
  • Skill files go in .claude/skills/ (project)
  • Condensed skills go in project_skills/ (for bootstrap)
  • Check unknowns before logging new ones
  • Commit after each goal (prevent drift)
  • Sentinel is now wired via MCP (EMPIRICA_EPISTEMIC_MODE=true)
  • PreToolCall hooks gate Edit/Write/Bash via CHECK

References

  • empirica --help - Full CLI reference
  • docs/architecture/separation-of-concerns.md - What goes where
  • docs/architecture/EPISTEMIC_AGENT_ARCHITECTURE.md - Turtle stack
  • docs/architecture/QDRANT_EPISTEMIC_INTEGRATION.md - Semantic search