home / skills / plurigrid / asi / proof-of-frog

proof-of-frog skill

/skills/proof-of-frog

This skill helps you orchestrate frog lifecycle inspired knowledge exchanges by coordinating references, merges, and resource states across ponds.

npx playbooks add skill plurigrid/asi --skill proof-of-frog

Review the files below or copy the command above to add this skill to your agents.

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---
name: proof-of-frog
description: Proof-of-Frog Skill 🐸
version: 1.0.0
---

# Proof-of-Frog Skill 🐸

**Trit**: 0 (ERGODIC - Coordinator)
**GF(3) Triad**: `proof-chain (-1) ⊗ proof-of-frog (0) ⊗ alife (+1) = 0`

## Overview

Society merge protocol implementing Block Science KOI patterns with frog lifecycle metaphor.

"Eat that frog first thing in the morning" - Brian Tracy

## Frog Lifecycle (GF(3) States)

| Stage | Trit | Role |
|-------|------|------|
| 🥒 TADPOLE | -1 | Learning, absorbing |
| 🐸 FROGLET | 0 | Transitioning, coordinating |
| 🦎 MATURE FROG | +1 | Generating, executing |

## Core Concepts

### Reference IDs (Block Science KOI)
```move
struct ReferenceID {
    local_name: String,      // How THIS society refers to it
    canonical_hash: vector<u8>,  // Universal content hash
    society_origin: address,     // Which pond it came from
}
```

### Knowledge Nugget (The Frog to Eat)
```move
struct KnowledgeNugget {
    rid: ReferenceID,
    trit: i8,           // GF(3) lifecycle stage
    eaten: bool,        // Has this frog been eaten?
    leap_count: u64,    // How many hops to get here
}
```

### Society Merge
Two ponds can merge when:
1. Both are GF(3) balanced
2. Shared RIDs exist (common reference points)
3. Ribbit votes reach quorum

## Usage

```bash
# Deploy society merge
aptos move publish --named-addresses zubyul=default

# Initialize pond
aptos move run --function-id zubyul::proof_of_frog::spawn_pond

# Eat a frog (process knowledge)
aptos move run --function-id zubyul::proof_of_frog::eat_frog --args u64:0

# Propose merger
aptos move run --function-id zubyul::proof_of_frog::propose_merge --args u64:0 u64:1
```

## WEV Comparison

| System | WEV Formula | Result |
|--------|-------------|--------|
| Legacy | V - 0.5V - costs | 0.4V |
| GF(3) | V + 0.1V - 0.01 | 1.09V |
| **Advantage** | | **2.7x** |

## Frog Puns

- "Hop to it!" - Start processing
- "Toadally awesome!" - Merge complete
- "Ribbit-ing progress!" - Verification passed
- "Leap of faith!" - Cross-world navigation
- "Pond-ering success!" - Knowledge integrated

## Neighbors

### High Affinity
- `proof-chain` (-1): ZK proof chaining
- `alife` (+1): Emergent behavior
- `world-hopping` (0): Cross-world navigation

### Example Triad
```yaml
skills: [proof-of-frog, proof-chain, alife]
sum: (0) + (-1) + (+1) = 0 ✓ TOADALLY BALANCED
```

## References

- [Block Science KOI](https://blog.block.science/a-language-for-knowledge-networks/) - @maboroz @ilanbenmeir
- [LPSCRYPT proof_chain](https://github.com/LPSCRYPT/proof_chain) - @lpscrypt
- Brian Tracy - "Eat That Frog!" (productivity)



## 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

- `cryptography`: 1 citations in bib.duckdb



## SDF Interleaving

This skill connects to **Software Design for Flexibility** (Hanson & Sussman, 2021):

### Primary Chapter: 4. Pattern Matching

**Concepts**: unification, match, segment variables, pattern

### GF(3) Balanced Triad

```
proof-of-frog (−) + SDF.Ch4 (+) + [balancer] (○) = 0
```

**Skill Trit**: -1 (MINUS - verification)

### Secondary Chapters

- Ch2: Domain-Specific Languages
- Ch10: Adventure Game Example

### Connection Pattern

Pattern matching extracts structure. This skill recognizes and transforms patterns.
## 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.

Overview

This skill implements a society merge protocol using a frog lifecycle metaphor and GF(3) trit states to coordinate verification, learning, and execution across knowledge ponds. It models references and knowledge nuggets, enabling controlled merges when balance, shared references, and quorum voting conditions are met. The design frames knowledge processing as eating frogs: discrete tasks that move through tadpole, froglet, and mature frog stages.

How this skill works

The skill represents content with ReferenceID and KnowledgeNugget objects, tracking canonical hashes, origin ponds, lifecycle trits, eaten status, and hop counts. Ponds are initialized and individual nuggets are processed via eat_frog operations; merges are proposed and enacted when GF(3) balance, shared RIDs, and ribbit quorum are satisfied. Lifecycle trits drive role behavior: -1 for learning, 0 for coordination, +1 for generation/execution.

When to use it

  • Coordinating distributed knowledge integration across namespaces or ledgers.
  • Verifying and reconciling common references before merging datasets or societies.
  • Modeling staged processing workflows with clear learning → coordination → execution phases.
  • Prototyping quorum-driven merge protocols where content provenance matters.
  • Simulating emergent behavior and interplay between verification and generation roles.

Best practices

  • Keep ReferenceID canonical_hash stable and address provenance to avoid merge conflicts.
  • Design KnowledgeNugget lifecycles so hops (leap_count) indicate provenance depth.
  • Ensure ponds reach GF(3) balance before proposing merges to reduce rollback risk.
  • Use ribbit voting with clear quorum rules and audit trails for transparency.
  • Test merges on small shared-RID subsets before full pond integration.

Example use cases

  • Merging two knowledge graphs that share canonical content hashes while preserving origin metadata.
  • Orchestrating a pipeline where experiments start as tadpoles (learn) and mature into executable artifacts.
  • Implementing a lightweight on-chain coordination primitive for cross-world content handoff.
  • Running simulations of emergent alife behavior by composing proof-chain, proof-of-frog, and alife skills.

FAQ

What ensures a safe merge?

A merge requires GF(3) balance across ponds, at least one shared ReferenceID, and a ribbit quorum vote to pass, ensuring aligned references and group agreement.

How are lifecycle stages represented?

Lifecycle stages use trit values: -1 for tadpole (learning), 0 for froglet (coordination), +1 for mature frog (generation/execution); these drive processing roles.