triadic-skill-loader
Manage and interleave agent skills using triadic logic.
Install
mkdir -p .claude/skills/triadic-skill-loader && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/16222" && unzip -o skill.zip -d .claude/skills/triadic-skill-loader && rm skill.zipInstalls to .claude/skills/triadic-skill-loader
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Triadic Skill LoaderKey capabilities
- →Load skills in balanced triads for each interaction
- →Select the next triad using a golden angle rotation strategy
- →Verify GF(3) balance for loaded triads
- →Integrate skill loading with pre-interaction hooks
- →Identify synergistic effects of loaded skill combinations
How it works
The skill loads three skills at a time for each interaction, selecting them from predefined triads using a golden angle rotation strategy. It ensures GF(3) balance and can be integrated via pre-interaction hooks.
Inputs & outputs
When to use triadic-skill-loader
- →Load balanced skills
- →Coordinate skill interaction
- →Optimize agent performance
About this skill
Triadic Skill Loader
Trit: 0 (ERGODIC) - Coordinates balanced skill loading
Principle: Load 3 skills at a time, every interaction, with GF(3) conservation.
Core Invariant
∀ interaction: load(skill₋₁) ⊗ load(skill₀) ⊗ load(skill₊₁) = 0 (mod 3)
Skill Triad Catalog
Structural Triads
| Minus (-1) | Ergodic (0) | Plus (+1) | Domain |
|---|---|---|---|
| structured-decomp | mutual-awareness-backlink | gh-interactome | Awareness |
| sheaf-cohomology | cognitive-superposition | gflownet | Intelligence |
| kolmogorov-compression | triad-interleave | curiosity-driven | Learning |
| segal-types | bumpus-narratives | world-hopping | Categories |
| persistent-homology | unworld | gay-mcp | Topology |
Execution Triads
| Minus (-1) | Ergodic (0) | Plus (+1) | Domain |
|---|---|---|---|
| clj-kondo-3color | acsets-relational-thinking | rama-gay-clojure | Clojure |
| three-match | specter-acset | bisimulation-game | Navigation |
| sheaf-laplacian | interactome-rl-env | jaxlife-open-ended | RL |
Loading Protocol
class TriadicSkillLoader:
"""Load skills in balanced triads every interaction."""
TRIADS = [
# Cognitive triad
("sheaf-cohomology", "cognitive-superposition", "gflownet"),
# Awareness triad
("structured-decomp", "mutual-awareness-backlink", "gh-interactome"),
# Interleaving triad
("kolmogorov-compression", "triad-interleave", "curiosity-driven"),
# Category triad
("segal-types", "bumpus-narratives", "world-hopping"),
# Game triad
("three-match", "bisimulation-game", "gay-mcp"),
]
def __init__(self, seed: int = 0x42D):
self.seed = seed
self.rng = SplitMix64(seed)
self.interaction_count = 0
self.loaded_triads = []
def next_triad(self) -> tuple:
"""Select next triad using golden angle rotation."""
index = int((self.interaction_count * 137.508) % len(self.TRIADS))
self.interaction_count += 1
return self.TRIADS[index]
def load_for_interaction(self) -> dict:
"""Load balanced triad for this interaction."""
minus, ergodic, plus = self.next_triad()
# Verify GF(3) balance
trit_sum = -1 + 0 + 1
assert trit_sum == 0, "Triad must be balanced"
self.loaded_triads.append((minus, ergodic, plus))
return {
"minus": {"skill": minus, "trit": -1},
"ergodic": {"skill": ergodic, "trit": 0},
"plus": {"skill": plus, "trit": 1},
"sum": 0,
"interaction": self.interaction_count
}
Interaction Pattern
Interaction 1:
└─ Load: cognitive-superposition (0), triad-interleave (+1), bisimulation-game (+1)
└─ Needs: sheaf-cohomology (-1) or similar to balance
Interaction 2:
└─ Load: structured-decomp (-1), mutual-awareness-backlink (0), gh-interactome (+1)
└─ GF(3) = -1 + 0 + 1 = 0 ✓
Interaction 3:
└─ Load: segal-types (-1), bumpus-narratives (0), world-hopping (+1)
└─ GF(3) = -1 + 0 + 1 = 0 ✓
Integration with Amp/Codex
Pre-Interaction Hook
# .ruler/hooks/pre-interaction.bb
(defn load-skill-triad [interaction-count]
(let [triads [["sheaf-cohomology" "cognitive-superposition" "gflownet"]
["structured-decomp" "mutual-awareness-backlink" "gh-interactome"]
["kolmogorov-compression" "triad-interleave" "curiosity-driven"]]
index (mod (int (* interaction-count 137.508)) (count triads))
[minus ergodic plus] (nth triads index)]
{:load [minus ergodic plus]
:gf3 0
:interaction interaction-count}))
Amp Skill Loading
# SKILL.md trigger pattern
triggers:
- every_interaction:
load_triads: true
strategy: golden_angle
seed: 0x42D
Synergistic Effects
When 3 skills are loaded together, they create emergent capabilities:
cognitive-superposition × triad-interleave × bisimulation-game
= Superposed skill states that can be interleaved and verified for equivalence
structured-decomp × mutual-awareness-backlink × gh-interactome
= Decomposed awareness graphs with contributor backlinks
sheaf-cohomology × bumpus-narratives × world-hopping
= Cohomological narrative verification across possible worlds
GF(3) Verification
function verify_triadic_loading(loader::TriadicSkillLoader)
total_trit = 0
for (minus, ergodic, plus) in loader.loaded_triads
trit_sum = -1 + 0 + 1
@assert trit_sum == 0 "Triad unbalanced"
total_trit += trit_sum
end
@assert total_trit == 0 "Overall GF(3) violated"
true
end
Commands
just load-triad # Load next balanced triad
just show-triads # Display all available triads
just verify-gf3 # Verify conservation
just golden-rotation SEED # Show golden angle rotation sequence
Files
triadic_skill_loader.py- Python implementationtriadic_skill_loader.bb- Babashka hooktriadic_skill_loader.jl- Julia ACSet integration
Skill Name: triadic-skill-loader Type: Meta-skill / Orchestration Trit: 0 (ERGODIC) Key Property: GF(3) = 0 per interaction, golden angle rotation
Para(Optic) atlas
Part of: para-mensch-commons.
When not to use it
- →When a specific skill needs to be loaded independently without triad balancing
- →When the user wants to manually select skills for each interaction
Limitations
- →Skill loading is constrained to predefined triads
- →Relies on a specific golden angle rotation for triad selection
- →GF(3) balance is a core invariant that must be maintained
How it compares
This skill implements a unique triadic loading protocol with GF(3) conservation and golden angle rotation to balance skill activation, providing a structured and emergent approach to skill orchestration, unlike direct skill invocation.
Compared to similar skills
triadic-skill-loader side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| triadic-skill-loader (this skill) | 0 | 2mo | Review | Advanced |
| using-superpowers | 95 | 3mo | No flags | Beginner |
| ultrawork | 11 | 2mo | No flags | Advanced |
| clawhub | 25 | 3mo | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
More by plurigrid
View all by plurigrid →You might also like
using-superpowers
obra
Use when starting any conversation - establishes mandatory workflows for finding and using skills, including using Skill tool before announcing usage, following brainstorming before coding, and creating TodoWrite todos for checklists
ultrawork
Yeachan-Heo
Parallel execution engine for high-throughput task completion
clawhub
openclaw
Use the ClawHub CLI to search, install, update, and publish agent skills from clawhub.com. Use when you need to fetch new skills on the fly, sync installed skills to latest or a specific version, or publish new/updated skill folders with the npm-installed clawhub CLI.
skill-installer
openai
Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos).
continuous-learning
affaan-m
Automatically extract reusable patterns from Claude Code sessions and save them as learned skills for future use.
memory-keeper-proactive-context-maintenance
b4CU-R4U
Automatically detect and maintain memory freshness by monitoring context staleness, significant code changes, task completions, and phase transitions. Proactively suggests and executes memory sync operations with user confirmation. Use when the user says "sync memory", "update context", or when the Skill detects that context is stale (>2 hours), significant changes have occurred (new commits), tasks completed, or major milestones reached. Replaces passive "context is stale" warnings with active maintenance.