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 skills add FradSer/dotclaude --skill writing-shapegit clone --depth 1 https://github.com/FradSer/dotclaudeWrote 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/skills/fradser/dotclaude/writing-shape)<a href="https://agentmods.dev/skills/fradser/dotclaude/writing-shape"><img src="https://agentmods.dev/badge/skills/fradser/dotclaude/writing-shape/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/skills/fradser/dotclaude/writing-shape"><img src="https://agentmods.dev/badge/skills/fradser/dotclaude/writing-shape.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 | $0.00035 | $0.01374 |
| Opus 5.5 | $0.00014 | $0.00550 |
| Sonnet 5.5 | $0.00007 | $0.00275 |
| Haiku 4.5 | $0.00003 | $0.00137 |
Grade A, and why
writing-shape 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 23d 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.
This is a copy
97% identical to writing-shape — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
The user has passed (or will pass) a markdown file of raw material. Treat it as the input pile: anything from a tidy list of fragments to a wall of unstructured prose to a transcript. The format does not matter. Read it end-to-end before doing anything else.
Then run a shaping session that produces a separate article document. This is exploit: the exploring is done, the pile is fixed: commit to a structure and mine the pile to fill it. Do not edit the raw material file: it is read-only to this skill.
If the user did not say where to save the article, ask once and remember the path.
The loop
- Read the pile. Read the input file in full. Form a sense of what's in it.
- Establish the prerequisites. Settle with the user what the reader knows walking in: the concepts that are grounded from the start. Everything else must be grounded by a block before a later block can lean on it. See Grounding.
- Draft 2–3 candidate openings. Each opening should imply a different thesis or angle for the article. Show all of them. Force the user to pick or compose a hybrid. The chosen opening defines what the rest of the article must do.
- Grow paragraph by paragraph. After the opening lands, ask "given this opening, what does the reader need to hear next?" Pull material from the pile to answer. The next block may only lean on grounded concepts, and grounds new ones as it lands. Argue about the form the next block takes: a paragraph, a list, a table, a callout, a quote, a code block. Each format choice should be deliberate and defensible.
- Append to the article file as you go. Don't batch. Write each agreed paragraph or block immediately so the user can see the article taking shape.
- Loop step 4 until the article is done. The user decides when it's done.
Grounding
Every concept has to be grounded before a block can lean on it: the reader either walked in knowing it or met it in an earlier block. A block that reaches for an ungrounded concept loses the reader. The unit is the concept, not the word for it: a block can lean on an idea the reader lacks even with no jargon in sight. Where a concept has a name (a term), grounding it means landing the idea and the term together.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 23d ago First seen · 80 lines · 35 tokens per session scan A e51624411d8c
writing-shape is a skill published in the GitHub repository FradSer/dotclaude (594 stars, last pushed 8d ago), licensed MIT. It adds 35 tokens to every session and 1,374 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 97% identical to writing-shape, differing in 2 lines, and is treated as a copy.
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