precompute-relationships

precompute-relationships is a skill for Claude Code from jimmc414/claude-code-plugin-marketplace. It costs 28 tokens per session (706 once invoked), scanned A, original, MIT.

A programming pattern for calculating fixed relationships once and reusing them later. For example, a Sudoku solver can precompute which cells share a row, column, or box.

In plain words
What is it for?
Use it for static graph links, grid neighbors, hierarchy relationships, or constraint peers when those relationships do not change while the program runs.
Why use it?
It avoids repeating the same relationship calculations during the program's main work, making repeated lookups simpler and faster.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the norvig-patterns plugin — 54 skills shipped together

Good fit Use it for static graph links, grid neighbors, hierarchy relationships, or constraint peers when those relationships do not change while the program runs.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jimmc414/claude-code-plugin-marketplace/precompute-relationships
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 jimmc414/claude-code-plugin-marketplace --skill precompute-relationships
Clone the repo
git clone --depth 1 https://github.com/jimmc414/claude-code-plugin-marketplace

Made for: Claude Code.

Or install norvig-patterns, the plugin that ships this one along with the rest of its 54 skills.

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 precompute-relationships

README.md
[![agentmods](https://agentmods.dev/badge/skills/jimmc414/claude-code-plugin-marketplace/precompute-relationships/github.svg)](https://agentmods.dev/skills/jimmc414/claude-code-plugin-marketplace/precompute-relationships)
Your own site
<a href="https://agentmods.dev/skills/jimmc414/claude-code-plugin-marketplace/precompute-relationships"><img src="https://agentmods.dev/badge/skills/jimmc414/claude-code-plugin-marketplace/precompute-relationships/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 precompute-relationships

Your own site · 80×15
<a href="https://agentmods.dev/skills/jimmc414/claude-code-plugin-marketplace/precompute-relationships"><img src="https://agentmods.dev/badge/skills/jimmc414/claude-code-plugin-marketplace/precompute-relationships.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 28 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 706 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.
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 $0.00028 $0.00706
Opus 5 $0.00014 $0.00353
Sonnet 5 $0.00006 $0.00141
Haiku 4.5 $0.00003 $0.00071

Measured 9d ago against content hash 91133c6ec69a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

precompute-relationships 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 9d 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.

plugins/norvig-patterns/skills/precompute-relationships/SKILL.md · 89 lines

How it starts

The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.

precompute-relationships

When to Use

  • Problem has fixed structure (grid, graph, hierarchy)
  • Same relationships queried repeatedly
  • Relationships can be computed from problem definition
  • Constraint problems with peers/neighbors
  • Any "what affects what" mapping

When NOT to Use

  • Relationships change during execution
  • Structure is too large to precompute
  • Only needed once

The Pattern

Compute all static relationships at module load time. Store in dicts for O(1) lookup.

# Define structure
rows = 'ABCDEFGHI'
cols = '123456789'

# Precompute all squares
squares = [r + c for r in rows for c in cols]

# Precompute all units (rows, cols, boxes)
unit_list = (
    [[r + c for c in cols] for r in rows] +  # Rows
    [[r + c for r in rows] for c in cols] +  # Columns
    [[r + c for r in rs for c in cs]         # Boxes
     for rs in ['ABC', 'DEF', 'GHI']
     for cs in ['123', '456', '789']]
)

# Precompute which units each square belongs to
units = {s: [u for u in unit_list if s in u] for s in squares}

# Precompute peers (squares that constrain this one)
peers = {s: set(sum(units[s], [])) - {s} for s in squares}

Example (from pytudes Sudoku.ipynb)

def cross(A, B):
    """Cross product of elements in A and B."""
    return [a + b for a in A for b in B]

digits = '123456789'
rows = 'ABCDEFGHI'
cols = digits

# All 81 squares
squares = cross(rows, cols)

# All 27 units
unitlist = ([cross(rows, c) for c in cols] +
            [cross(r, cols) for r in rows] +
            [cross(rs, cs)
             for rs in ('ABC', 'DEF', 'GHI')
             for cs in ('123', '456', '789')])

# units[s] = list of 3 units containing square s
units = {s: [u for u in unitlist if s in u]
         for s in squares}

# peers[s] = set of 20 squares that see square s
peers = {s: set(sum(units[s], [])) - {s}
         for s in squares}

# Now constraint propagation is fast:
def eliminate(values, s, d):
    for peer in peers[s]:  # O(1) lookup!
        eliminate(values, peer, d)

Read the full file on GitHub · 89 lines

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. 9d ago First seen · 89 lines · 28 tokens per session scan A 91133c6ec69a

Subscribe to this mod's changes

precompute-relationships is a skill published in the GitHub repository jimmc414/claude-code-plugin-marketplace (4 stars, last pushed yesterday), licensed MIT. It adds 28 tokens to every session and 706 once invoked, about $0.0001 per session on Opus 5. 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 2026-08-31.

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