spectral-random-walker

spectral-random-walker is a skill for Codex from plurigrid/asi. It costs 0 tokens per session (693 once invoked), scanned A, original, MIT.

A Julia analysis tool that uses random walks through a graph of proofs to find related theorems. A random walk repeatedly moves between connected nodes, while spectral analysis helps describe how broadly it explores the graph.

In plain words
What is it for?
Use it to sample proof paths, estimate graph-mixing behavior, cluster theorems by shared visits, and generate analysis reports.
Why use it?
It helps navigate large proof collections where manually finding nearby or related theorems is difficult.

Skill for Codex

Written for Codex: installed under .codex/.

Good fit Use it to sample proof paths, estimate graph-mixing behavior, cluster theorems by shared visits, and generate analysis reports.

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Install with agentmods
npx agentmods add skills/plurigrid/asi/spectral-random-walker
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add plurigrid/asi --skill spectral-random-walker
Clone the repo
git clone --depth 1 https://github.com/plurigrid/asi

Made for: Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for spectral-random-walker

README.md
[![agentmods](https://agentmods.dev/badge/skills/plurigrid/asi/spectral-random-walker/github.svg)](https://agentmods.dev/skills/plurigrid/asi/spectral-random-walker)
Your own site
<a href="https://agentmods.dev/skills/plurigrid/asi/spectral-random-walker"><img src="https://agentmods.dev/badge/skills/plurigrid/asi/spectral-random-walker/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for spectral-random-walker

Your own site · 80×15
<a href="https://agentmods.dev/skills/plurigrid/asi/spectral-random-walker"><img src="https://agentmods.dev/badge/skills/plurigrid/asi/spectral-random-walker.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 693 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00000 $0.00693
Opus 5 $0.00000 $0.00347
Sonnet 5 $0.00000 $0.00139
Haiku 4.5 $0.00000 $0.00069

Measured 8d ago against content hash 835de2214478, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

spectral-random-walker scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

ies/music-topos/.codex/skills/spectral-random-walker/SKILL.md · 93 lines

How it starts

The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Spectral Random Walker

Category: Theorem Discovery + Comprehension Type: Random Walk Analysis Language: Julia Status: Production Ready Version: 1.0.0 Date: December 22, 2025

Overview

Integrates spectral gaps with random walk theory using the Benjamin Merlin Bumpus comprehension model. Samples proof space via random walks to discover related theorems through co-visitation patterns, enabling "comprehension neighborhoods" - clusters of theorems that are naturally explored together.

Key Data Structures

struct RandomWalkAnalysis
    start_node::Int
    current_node::Int
    visited_path::Vector{Int}
    visit_counts::Dict{Int, Int}
    transition_count::Int
    stationary_approximation::Dict{Int, Float64}
end

Key Functions

  • estimate_mixing_time(gap, n_nodes): Mixing time from spectral gap
  • simulate_random_walk(adjacency, start, steps): Uniform neighbor selection
  • sample_proof_paths(adjacency, num_samples): Metropolis-Hastings sampling
  • comprehension_discovery(adjacency, gap): Co-visitation clustering
  • generate_random_walk_report(): Analysis report generation

Mathematical Foundation

Benjamin Merlin Bumpus Comprehension Model

Three perspectives on proof connectivity:

  1. Spectral (gap): "How optimal?" - measures expansion property
  2. Combinatorial (Möbius): "Where tangled?" - identifies problem paths
  3. Probabilistic (random walks): "How explore?" - discovery mechanism

Mixing Time Theory

mixing_time ≈ log(n) / spectral_gap

High gap  → Fast mixing → Easy theorem discovery
Low gap   → Slow mixing → Tangled dependencies impede exploration

Co-visitation Matrix

  • Records theorems frequently reached together in random walks
  • Cluster via 75th percentile threshold
  • Forms "comprehension regions" - natural theorem groupings

Usage

using SpectralRandomWalk

# 1. Check system health
gap = SpectralAnalyzer.analyze_all_provers()["lean4"]

# 2. Estimate exploration time
mixing_time = estimate_mixing_time(gap, n_theorems)

# 3. Sample comprehension regions
comprehension = comprehension_discovery(adjacency, gap)

# 4. Discover related theorems
region = comprehension["comprehension_regions"][theorem_id]
related = sample(region, 10)  # 10 related theorems

Read the full file on GitHub · 93 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 93 lines · 0 tokens per session scan A 835de2214478

Subscribe to this mod's changes

spectral-random-walker is a skill published in the GitHub repository plurigrid/asi (64 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 693 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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