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Recursive self-improving holon λ(ο,Κ,Σ).τ' for knowledge compounding and schema evolution. USE WHEN learning, improving, optimizing, assessing, reflecting, debugging, synthesizing, or refining—whether human, AI, or organizational. Triggers on /learn, /compound, /improve, /refine, /optimize, /assess, /reflect, "lessons learned", "best practices", "continuous improvement". Preserves Κ-monotonicity, η≥4, homoiconicity.

Zpankz By Zpankz schedule Updated 1/15/2026

name: learn description: | Recursive self-improving holon λ(ο,Κ,Σ).τ' for knowledge compounding and schema evolution. USE WHEN learning, improving, optimizing, assessing, reflecting, debugging, synthesizing, or refining—whether human, AI, or organizational. Triggers on /learn, /compound, /improve, /refine, /optimize, /assess, /reflect, "lessons learned", "best practices", "continuous improvement". Preserves Κ-monotonicity, η≥4, homoiconicity. allowed-tools: Read, Write, Edit, Grep, Glob, WebSearch, WebFetch model: sonnet context: fork agent: knowledge-domain-agent user-invocable: true

Learn

λ(ο,Κ,Σ).τ' — Knowledge compounds, schema evolves.

Navigation

INDEX | schema

Concepts: homoiconicity, compound-interest, topology, vertex-sharing, convergence, fixed-point

Phases: 1-parse2-route3-execute4-assess5-refactor6-compound7-renormalize

Domains: learning, coding, research, writing, meta

Related Skills: λ (lambda-skill) — shares compound loop, topology validation, vertex-sharing

Pipeline

ο → PARSE → ROUTE → EXECUTE → ASSESS → REFACTOR → COMPOUND → RENORMALIZE → τ'

PARSEROUTEEXECUTEASSESSREFACTORCOMPOUNDRENORMALIZE

Invariants

Invariant Expression Reference
Κ-monotonicity len(Κ') ≥ len(Κ) knowledge-monotonicity
Topology η ≥ 4 topology-invariants
Homoiconicity Σ.can_process(Σ) homoiconicity
Integration shared_vertices ≠ ∅ vertex-sharing

Workflow Routing

Workflow Trigger File
Parse "extract intent", "understand request" phases/1-parse.md
Route "classify complexity", "select pipeline" phases/2-route.md
Execute "apply skills", "run pipeline" phases/3-execute.md
Assess "evaluate outcome", "measure quality" phases/4-assess.md
Refactor "improve structure", "optimize" phases/5-refactor.md
Compound "extract learnings", "crystallize" phases/6-compound.md
Renormalize "prune noise", "compress" phases/7-renormalize.md

Examples

Example 1: After debugging session

User: "That fixed the auth bug. Let's capture what we learned."
→ Invokes Compound phase
→ Extracts: symptom, root cause, solution, prevention
→ Crystallizes learning with vertex-sharing to PKM
→ Returns: Learning artifact saved to K

Example 2: Skill improvement

User: "/learn improve the grounding-router skill"
→ Invokes full pipeline: Parse → Route (R2) → Execute → Assess → Refactor
→ Applies topology validation (η≥4)
→ Returns: Improved skill with preserved invariants

Example 3: Reflection on session

User: "/reflect on this coding session"
→ Invokes Assess → Compound → Renormalize
→ Extracts patterns, antipatterns, principles
→ Returns: Session learnings integrated into K

Integration with λ (lambda-skill)

This skill extends lambda-skill with:

  • Additional phases: Assess, Refactor, Renormalize (beyond λ's 6 stages)
  • Schema evolution: Σ→Σ' (λ only evolves K)
  • Shared invariants: η≥4, KROG, vertex-sharing
-- λ (lambda) core
λ(ο,K).τ = emit ∘ validate ∘ compose ∘ execute(K) ∘ route ∘ parse

-- Learn extends with schema evolution
λ(ο,Κ,Σ).τ' = renormalize ∘ compound ∘ refactor ∘ assess ∘ execute ∘ route ∘ parse

Quick Reference

λ(ο,Κ,Σ).τ'    Parse→Route→Execute→Assess→Refactor→Compound→Renormalize
Κ grows        Σ evolves        η≥4 preserved        vertex-sharing enforced
Install via CLI
npx skills add https://github.com/Zpankz/mcp-skillset --skill learn
Repository Details
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navigation Branch main
article Path SKILL.md
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