llm-docs-optimizer: Instructions file for Claude Code

CLAUDE.md

llm-docs-optimizer CLAUDE.md is an instructions file for Claude Code from alonw0/llm-docs-optimizer. It costs 1,380 tokens per session, scanned A, original, MIT.

A set of instructions for a Claude Code plugin whose main code is written in Markdown. It helps improve project documentation for AI coding assistants and creates llms.txt navigation files.

In plain words
What is it for?
Use it to optimize documentation against Context7's quality measures and generate llms.txt files that help language models find their way around project docs.
Why use it?
It gives the agent a defined way to understand and improve documentation in a project that has no usual compiled code or test setup.

Instructions file for Claude Code

Written for Claude Code: Claude Code plugin machinery. Also seen: reads .claude/ paths; mentions .claude-plugin; mentions CLAUDE.md.

This is alonw0/llm-docs-optimizer's own configuration. It tells Claude Code how to work on llm-docs-optimizer itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything llm-docs-optimizer configures →

Reuse

Borrowing it

Nothing to install: this file belongs to alonw0/llm-docs-optimizer. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/alonw0/llm-docs-optimizer/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/alonw0/llm-docs-optimizer

Made for: Claude Code.

Wrote this? Show the measurements

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README.md
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Per session 1,380 This file is loaded in full into every session.
When invoked 1,380 The same file — it is already loaded in full.
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 $0.01380 $0.01380
Opus 5.5 $0.00552 $0.00552
Sonnet 5.5 $0.00276 $0.00276
Haiku 4.5 $0.00138 $0.00138

Measured 2mo ago against content hash a0b7cdbba354, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

llm-docs-optimizer CLAUDE.md 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 2mo 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.

CLAUDE.md · 153 lines

How it starts

The opening of the file, as written. The whole thing — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Project Overview

llm-docs-optimizer is a Claude Code plugin that optimizes documentation for AI coding assistants (Claude, GitHub Copilot, etc.). It provides two core capabilities:

  1. C7Score Optimization: Transforms documentation to score highly on Context7's benchmark - the leading quality metric for AI-assisted coding documentation
  2. llms.txt Generation: Creates standardized navigation files (llmstxt.org format) that help LLMs quickly understand and navigate project documentation

Architecture

This is NOT a Traditional Codebase

This is a Claude Code skill/plugin where the "code" is markdown. There are no build tools, test frameworks, or compilation steps for the main plugin.

skills/llm-docs-optimizer/
├── SKILL.md (21,827 lines)    # Main skill logic - the "code"
├── references/                 # Knowledge base
│   ├── c7score_metrics.md     # Scoring rubrics for 5 metrics
│   ├── optimization_patterns.md # 20+ transformation examples
│   └── llmstxt_format.md      # llms.txt specification
├── examples/                   # Before/after samples
└── scripts/
    └── analyze_docs.py        # Optional Python analysis tool

Component Interaction

  • SKILL.md: Contains structured workflows for both optimization and generation. This is where all logic lives.
  • Reference Materials: Knowledge base that SKILL.md references during execution
  • Python Script: Optional standalone tool for automated documentation scanning
  • c7score/: Separate TypeScript reference implementation (Upstash's package) - not directly used by the skill

Key Architectural Pattern: Structured Workflows

C7Score Optimization (6 Steps):

  1. Analyze current documentation
  2. Generate 15-20 developer questions
  3. Map questions to existing snippets
  4. Optimize based on priority (80% weight on question-answering)
  5. Validate optimizations
  6. Evaluate c7score impact with before/after scoring

Read the full file on GitHub · 153 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. 2mo ago First seen · 153 lines · 1,380 tokens per session scan A a0b7cdbba354

Subscribe to this mod's changes

llm-docs-optimizer CLAUDE.md is an instructions file published in the GitHub repository alonw0/llm-docs-optimizer (63 stars, last pushed 11mo ago), licensed MIT. It adds 1,380 tokens to every session, about $0.0055 per session on Opus 5.5. 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 2026-08-30.

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