Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add OC-NeuralSense/reader-first-writing-skills/plugin install reader-first-writingWrote 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/oc-neuralsense/reader-first-writing-skills/shape-and-close)<a href="https://agentmods.dev/skills/oc-neuralsense/reader-first-writing-skills/shape-and-close"><img src="https://agentmods.dev/badge/skills/oc-neuralsense/reader-first-writing-skills/shape-and-close/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/oc-neuralsense/reader-first-writing-skills/shape-and-close"><img src="https://agentmods.dev/badge/skills/oc-neuralsense/reader-first-writing-skills/shape-and-close.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 | $0.00180 | $0.02234 |
| Opus 5 | $0.00090 | $0.01117 |
| Sonnet 5 | $0.00036 | $0.00447 |
| Haiku 4.5 | $0.00018 | $0.00223 |
Grade A, and why
shape-and-close 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 11d 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 — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
shape-and-close
Purpose
Decide the two genre-informed "dials" of a document (how much visible apparatus it carries and how hard its ending pushes) and map the validated argument hierarchy onto an ordered section-and-paragraph layout (CAP-21). This is a generative skill: it sets shape, not sentences, and it holds meaning constant. Crucially, it exposes signpost density and emotive-close force as settings flagged for human ratification; it does not silently hard-code them.
When to use
- The apparatus question ("how much heading/numbering?") or the closing question ("flat summary or a call to act?") is live, and genre + aim are known.
- A plan needs its hierarchy turned into a checkable section/paragraph layout for the plan-document workflow to hand off.
When NOT to use (routing non-triggers)
- The whole structure still needs building -> build-argument.
- A full evaluation or ship decision is wanted -> review-document.
- Sentence-level flow/clarity -> revise-prose.
Inputs
plan_or_draft(required: ideally an argument-blueprint with a validated hierarchy)genre(required: business_analytical | academic | general_explanatory | technical_documentation)length(short | long)read_mode(scanned | linear: ASK if absent; it drives density)communicative_aim(reveal | act: drives the close)
Workflow
- Confirm the routing signals. If
read_modeorcommunicative_aimis missing and it changes the recommendation, ASK; do not infer. - Set apparatus density (light | moderate | heavy) from genre, length, and read-mode. Emit it as a ratifiable setting with the reasoning, not a fixed verdict.
- Design the close (presentational | action_seeking) from the aim. Emit the emotive/action force as a ratifiable setting with its default.
- Map the layout (CAP-21). For each section, in order: name its function, list the claim ids it carries, and give an ordered paragraph-level plan. Every heading and topic sentence must carry a real claim, never a generic label.
- Emit the density recommendation, the closing design, and the layout_map into the argument-blueprint fields, each flagged where human ratification is expected.
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.
- 11d ago First seen · 178 lines · 180 tokens per session scan A fbe460523984
shape-and-close is a skill published in the GitHub repository OC-NeuralSense/reader-first-writing-skills (1 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 180 tokens to every session and 2,234 once invoked, about $0.0009 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 2026-08-31.
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