Borrowing it
Nothing to install: this file belongs to WomenDefiningAI/claudecode-writer. 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/WomenDefiningAI/claudecode-writer/main/CLAUDE.mdgit clone --depth 1 https://github.com/WomenDefiningAI/claudecode-writerWrote 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/womendefiningai/claudecode-writer/claude-md)<a href="https://agentmods.dev/instructions/womendefiningai/claudecode-writer/claude-md"><img src="https://agentmods.dev/badge/instructions/womendefiningai/claudecode-writer/claude-md.svg" alt="Measured on agentmods" 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 | $0.00290 | $0.00290 |
| Opus 5 | $0.00145 | $0.00145 |
| Sonnet 5 | $0.00058 | $0.00058 |
| Haiku 4.5 | $0.00029 | $0.00029 |
Grade A, and why
claudecode-writer 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 7d 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.
What it actually says
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
Content Creation System
System Overview
This workspace transforms ideas into multi-format content:
- Raw notes → Theme extraction → Research → Long-form article → Platform-specific versions
- All brand/voice guidelines live in @context/
- Agents handle platform optimization
Workflow Commands
/extract-themes- Analyze raw notes in /rawnotes to identify patterns and content opportunities/research [topic]- Develop and refine ideas from themes or new topics/write- Create comprehensive article- Auto-generates: LinkedIn, Newsletter, Twitter/X, Podcast Q&A
Context Architecture
Always reference these for consistency:
- @context/writing-examples.md - Real examples across platforms that demonstrate voice and style
- @context/research-sources.md - Priority newsletters and sources to check first during research
Agent Specializations
linkedin-repurposer: Professional networking optimizationnewsletter-repurposer: Email engagement specialistconversational-repurposer: Social media posts and podcast Q&A scripts
Development Guidelines
- Never duplicate context information - always reference source files
- Maintain consistency across all generated formats
- Each agent should specialize in their platform's unique requirements
- Content quality gates should validate against brand guidelines before output
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.
- 7d ago First seen · 33 lines · 290 tokens per session scan A 3d43aea3d7bb
claudecode-writer CLAUDE.md is an instructions file published in the GitHub repository WomenDefiningAI/claudecode-writer (220 stars, last pushed 1y ago), licensed MIT. It adds 290 tokens to every session, about $0.0014 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 2026-08-30.
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