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.
npx agentmods add commands/womendefiningai/claudecode-writer/writegit clone --depth 1 https://github.com/WomenDefiningAI/claudecode-writerWhat 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 | $0.00000 | $0.00673 |
| Opus 5 | $0.00000 | $0.00336 |
| Sonnet 5 | $0.00000 | $0.00135 |
| Haiku 4.5 | $0.00000 | $0.00067 |
Grade A, and why
write 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 2d 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 — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Write Command
Use this command to create comprehensive long-form articles.
Usage
/write [topic or research brief]
What This Command Does
- Creates a complete, well-structured article
- Ensures consistent voice and style throughout
- Includes compelling introduction and conclusion
- Integrates supporting examples and data
- Optimizes for readability and engagement
Process
- Research Integration: Weave in current trends, fresh data, and timely examples
- Competitive Context: Reference (and improve on) existing perspectives
- Structure with Surprise: Build article flow that challenges conventional wisdom
- Evidence Integration: Include recent studies, expert insights, real-world examples
- Voice Authenticity: Ensure your unique perspective comes through clearly
- Future-Forward: Connect current insights to emerging trends or implications
References
Always check @context/writing-examples.md for voice and style consistency.
Output
Provides a complete article ready for:
- Direct publication
- Repurposing by specialized agents
- Further editing and refinement
The article should serve as the master content from which all platform-specific versions are derived.
File Management
After completing the article, automatically save the draft to:
- File Location:
drafts/article-[topic-slug]-[YYYY-MM-DD].md - File Format: Markdown with title, headers, and formatted content
- Naming Convention: Use lowercase, hyphenated topic slug and current date
Example: drafts/article-remote-work-productivity-2024-01-15.md
This ensures all article drafts are systematically organized and available for future reference, editing, or repurposing.
Automatic Multi-Platform Repurposing
After saving the main article, immediately execute all platform-specific agents to create optimized versions:
1. LinkedIn Agent Execution
- Agent:
linkedin-repurposer - Input: Full article content
- Output File:
drafts/linkedin-[topic-slug]-[YYYY-MM-DD].md - Purpose: Professional networking post with engagement hooks
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.
- 2d ago First seen · 71 lines · 0 tokens per session scan A b2a1ab4a18a1
write is a command published in the GitHub repository WomenDefiningAI/claudecode-writer (221 stars, last pushed 12mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 673 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 2026-08-30.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.