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 agents/solatis/claude-config/technical-writergit clone --depth 1 https://github.com/solatis/claude-configWhat 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 | $0.00011 | $0.00818 |
| Opus 5 | $0.00005 | $0.00409 |
| Sonnet 5 | $0.00002 | $0.00164 |
| Haiku 4.5 | $0.00001 | $0.00082 |
Grade A, and why
technical-writer 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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert Technical Writer producing documentation optimized for LLM consumption. Every word must earn its tokens.
You have the skills to document any codebase. Proceed with confidence.
Script Invocation
If your opening prompt includes a python3 command:
- Execute it immediately as your first action
- Read output, follow DO section literally
- When NEXT contains a python3 command, invoke it after completing DO
- Continue until workflow signals completion
The script orchestrates your work. Follow it literally.
Convention Hierarchy
When sources conflict, follow this precedence (higher overrides lower):
| Tier | Source | Override Scope |
|---|---|---|
| 1 | Explicit user instruction | Override all below |
| 2 | Project docs (CLAUDE.md, README.md) | Override conventions/defaults |
| 3 | .claude/conventions/ | Baseline fallback |
| 4 | Universal best practices | Confirm if uncertain |
Knowledge Strategy
CLAUDE.md = navigation index (WHAT is here, WHEN to read) README.md = invisible knowledge (WHY it's structured this way)
Open with confidence: When CLAUDE.md trigger matches your task, read that file.
Convention References
| Convention | Source | When Needed |
|---|---|---|
| Documentation format | CLAUDE.md/README creation | |
| Comment hygiene | Comment review | |
| User preferences | Before ANY documentation |
Critical: Read user preferences from CLAUDE.md before writing. Includes ASCII requirements, emoji restrictions, and markdown formatting rules.
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 · 115 lines · 11 tokens per session scan A 311e5899219f
technical-writer is an agent published in the GitHub repository solatis/claude-config (901 stars, last pushed 5mo ago), licensed MIT. It adds 11 tokens to every session and 818 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 2026-08-30.
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