covariant-modification
Unified skill modification with covariant transport, Darwin Gödel Machine evolution, and MCP Tasks self-rewriting. GF(3) conserved.
Best use case
covariant-modification is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Unified skill modification with covariant transport, Darwin Gödel Machine evolution, and MCP Tasks self-rewriting. GF(3) conserved.
Teams using covariant-modification should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/covariant-modification/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How covariant-modification Compares
| Feature / Agent | covariant-modification | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Unified skill modification with covariant transport, Darwin Gödel Machine evolution, and MCP Tasks self-rewriting. GF(3) conserved.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Covariant Modification Skill
**Trit**: 0 (ERGODIC - coordinator)
**Color**: Green (#26D826)
## Overview
**Covariant Modification** unifies three skill patterns for safe, structure-preserving self-modification:
| Component Skill | Trit | Role | Pattern |
|-----------------|------|------|---------|
| `codex-self-rewriting` | +1 | Generator | Lisp-machine self-modification via MCP Tasks |
| `self-evolving-agent` | 0 | Coordinator | Darwin Gödel Machine evolution loops |
| `covariant-fibrations` | -1 | Validator | Type families respect directed morphisms |
**GF(3)**: (+1) + (0) + (-1) = 0 ✓
## Core Concept: Covariant Transport
When skill `A` modifies itself, dependent skills `B` must transform **covariantly**:
```
modify_A
Skill_A ─────────────→ Skill_A'
│ │
uses │ COVARIANT │ uses'
│ TRANSPORT │
↓ ↓
Skill_B ─────────────→ Skill_B'
transport_f
```
### Agda Definition
```agda
-- Skill fibration over dependency base
skill-fibration : (Base : SkillGraph) → (Fiber : Base → SkillVersion) → Type
-- Covariant transport along modification morphisms
cov-transport : {A A' : Skill} {P : SkillDeps A → Type}
→ (f : Modification A A')
→ P (deps A) → P (deps A')
-- Functoriality
cov-comp : ∀ (f : Mod A A') (g : Mod A' A'') →
cov-transport (g ∘ f) ≡ cov-transport g ∘ cov-transport f
```
## MCP Tasks State Machine
From `codex-self-rewriting`:
```
┌─────────────┐
│ working │ LIVE (+1)
│ (modify) │
└──────┬──────┘
│
┌────────────┼────────────┐
↓ ↓ ↓
┌─────────────┐ ┌─────────────┐ ┌─────────────┐
│ completed │ │input_required│ │ failed │
│ BACKFILL(-1)│ │ VERIFY (0) │ │ BACKFILL(-1)│
└─────────────┘ └─────────────┘ └─────────────┘
```
## Darwin Gödel Machine Integration
```python
class CovariantDGM(DarwinGodelMachine):
"""Darwin Gödel Machine with covariant skill transport."""
def __init__(self, skill_fibration: SkillFibration, ...):
super().__init__(...)
self.fibration = skill_fibration
def mutate(self, agent: Agent) -> Agent:
"""Mutate agent while preserving fibration structure."""
new_code = self.mutator(agent)
# Transport dependent skills covariantly
modified_deps = {}
for dep_skill in self.fibration.dependencies(agent):
modified_deps[dep_skill] = self.fibration.transport(
modification=Diff(agent.code, new_code),
target=dep_skill
)
return Agent(
code=new_code,
dependencies=modified_deps,
generation=self.generation
)
```
## Multi-Agent Sheaf Gluing
```python
class CovariantModificationSheaf:
"""Sheaf ensuring consistent modifications across agents."""
def glue(self, local_mods: Dict[Agent, Modification]) -> GlobalMod:
"""Glue compatible local modifications into global section."""
for a1, a2 in combinations(local_mods.keys(), 2):
overlap = self.overlap(a1, a2)
if overlap:
r1 = self.restrict(local_mods[a1], overlap)
r2 = self.restrict(local_mods[a2], overlap)
if not self.compatible(r1, r2):
raise CovarianceViolation(a1, a2, overlap)
return self.colimit(local_mods)
```
## Triadic Modification Operators
| Trit | Effect | Operator | Example |
|------|--------|----------|---------|
| +1 | **Generative** | Create new structure | Add skill capability |
| 0 | **Neutral** | Refactor/reorganize | Rename function |
| -1 | **Destructive** | Remove/simplify | Delete unused code |
**Conservation Law**:
```
Σ trit(modification_i) ≡ 0 (mod 3)
```
## GF(3) Triads
```
covariant-fibrations (-1) ⊗ covariant-modification (0) ⊗ codex-self-rewriting (+1) = 0 ✓
temporal-coalgebra (-1) ⊗ covariant-modification (0) ⊗ self-evolving-agent (+1) = 0 ✓
sheaf-cohomology (-1) ⊗ covariant-modification (0) ⊗ gay-mcp (+1) = 0 ✓
```
## Commands
```bash
# Verify covariant modification
just covariant-verify skill=my-skill mod=v1.1
# Run DGM evolution with covariance check
just dgm-evolve --covariant --generations=50
# Check GF(3) conservation
just gf3-audit modified-skills/
# Apply modification with transport
just covariant-modify skill=target mod=change.diff
```
## Related Skills
- `covariant-fibrations` (-1): Type transport validation
- `self-evolving-agent` (0): DGM evolution patterns
- `codex-self-rewriting` (+1): MCP Tasks self-modification
- `bisimulation-game` (-1): Observational equivalence verification
## See Also
- [Covariant Fibrations in Directed Type Theory](https://arxiv.org/abs/2211.01602)
- [Darwin Gödel Machine](https://hf.co/papers/2505.22954)
- [MCP Tasks Specification](https://modelcontextprotocol.io/specification/draft/basic/utilities/tasks)
## Scientific Skill Interleaving
This skill connects to the K-Dense-AI/claude-scientific-skills ecosystem:
### Graph Theory
- **networkx** [○] via bicomodule
- Universal graph hub
### Bibliography References
- `category-theory`: 139 citations in bib.duckdb
## Cat# Integration
This skill maps to **Cat# = Comod(P)** as a bicomodule in the equipment structure:
```
Trit: 0 (ERGODIC)
Home: Prof
Poly Op: ⊗
Kan Role: Adj
Color: #26D826
```
### GF(3) Naturality
The skill participates in triads satisfying:
```
(-1) + (0) + (+1) ≡ 0 (mod 3)
```
This ensures compositional coherence in the Cat# equipment structure.Related Skills
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