Borrowing it
Nothing to install: this file belongs to ginobefun/deep-reading-analyst-skill. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ginobefun/deep-reading-analyst-skill/main/CLAUDE.mdgit clone --depth 1 https://github.com/ginobefun/deep-reading-analyst-skillWrote 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.
[](https://agentmods.dev/instructions/ginobefun/deep-reading-analyst-skill/claude-md)<a href="https://agentmods.dev/instructions/ginobefun/deep-reading-analyst-skill/claude-md"><img src="https://agentmods.dev/badge/instructions/ginobefun/deep-reading-analyst-skill/claude-md/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.
<a href="https://agentmods.dev/instructions/ginobefun/deep-reading-analyst-skill/claude-md"><img src="https://agentmods.dev/badge/instructions/ginobefun/deep-reading-analyst-skill/claude-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.02231 | $0.02231 |
| Opus 5.5 | $0.00892 | $0.00892 |
| Sonnet 5.5 | $0.00446 | $0.00446 |
| Haiku 4.5 | $0.00223 | $0.00223 |
Grade A, and why
deep-reading-analyst-skill 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 285 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
Deep Reading Analyst is a Claude AI skill (.skill file) that provides systematic framework for deep analysis of articles, papers, and long-form content using multiple thinking models. It transforms surface-level reading into deep learning through structured workflows.
Core Purpose
This skill guides users through a 5-step analysis process using 10+ proven thinking frameworks:
Quick Analysis (15min):
- SCQA Framework (structure thinking)
- 5W2H Analysis (completeness check)
Standard Analysis (30min):
- Critical Thinking (argument evaluation, logical fallacy detection)
- Inversion Thinking (risk and failure mode analysis)
Deep Analysis (60min):
- Mental Models (multi-discipline perspectives: physics, biology, psychology, economics)
- First Principles (assumption stripping, essence extraction)
- Systems Thinking (causal loops, knowledge connections)
- Six Thinking Hats (multi-perspective evaluation)
Research Level (120min+):
- Cross-Source Comparison (multi-article synthesis)
Repository Structure
Source Files
src/deep-reading-analyst/- Source files for the skill (tracked in Git)SKILL.md- Main workflow and decision treereferences/- Detailed framework documentation (10+ frameworks)scqa_framework.md- McKinsey structure thinking (NEW!)5w2h_analysis.md- Completeness check with 7 questions (NEW!)critical_thinking.md- Argument analysis frameworkinversion_thinking.md- Charlie Munger's risk analysis (NEW!)mental_models.md- 30+ models from multiple disciplines (NEW!)first_principles.md- Elon Musk's assumption identificationsystems_thinking.md- Relationship mapping and causal loopssix_hats.md- Edward de Bono's multi-perspective protocoloutput_templates.md- 8 different output formatscomparison_matrix.md- Multi-source comparison methodology
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.
- 1mo ago First seen · 285 lines · 2,231 tokens per session scan A 77fc21867ff6
deep-reading-analyst-skill CLAUDE.md is an instructions file published in the GitHub repository ginobefun/deep-reading-analyst-skill (357 stars, last pushed 11mo ago), licensed MIT. It adds 2,231 tokens to every session, about $0.0089 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.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.