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/revise-prose)<a href="https://agentmods.dev/skills/oc-neuralsense/reader-first-writing-skills/revise-prose"><img src="https://agentmods.dev/badge/skills/oc-neuralsense/reader-first-writing-skills/revise-prose/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/revise-prose"><img src="https://agentmods.dev/badge/skills/oc-neuralsense/reader-first-writing-skills/revise-prose.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 | $0.00191 | $0.02524 |
| Opus 5 | $0.00096 | $0.01262 |
| Sonnet 5 | $0.00038 | $0.00505 |
| Haiku 4.5 | $0.00019 | $0.00252 |
Grade A, and why
revise-prose 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 — 198 lines — stays where its author put it; the contents beside it link to each section on GitHub.
revise-prose
Purpose
Repair the prose surface of a passage (its coherence, sentence geometry, word choice, length, thinness, or correctness) while holding the meaning exactly constant. This is a revisional skill working one plane only: it changes how a fixed set of claims is rendered, never what is claimed or how the argument is arranged. It emits the revised passage and a change-report that classifies every edit.
Task-mode handling (five modes, one skill)
The caller supplies task_mode; if absent, infer it from the request phrasing
and confirm. Each mode carries the same strict fidelity gate.
- cohere: "the flow is broken." Restore recoverable coherence: hold a stable topic string in or near the subject slot, anchor new material to given, repair paragraph bridges, and mark each intended relation once. Never insert a connective that names a relation the content does not actually carry.
- clarify: "make it clearer." Remove misparse (garden-path) traps and deep center-embedding, reconcile end-weight with given-before-new, split overgrown trees when held-open load is high. Keep every participant role and referent intact; distinguish a garden path (re-insert a cue) from genuine structural ambiguity (rebuild to one tree).
- compress: "cut it down." Delete only words that carry no meaning and no
parsing value. Keep every structure-marking word (the
thatthat blocks a misparse, the preposition that fixes attachment) and every qualifier, hedge, scope limit, condition, and exception. Length is measured in reader work, not word count. - expand: "it's too thin." Close the named expert blind spot with concrete, picturable material the reader needs: a definition, a worked instance, a laid given ground. Never pad, and never invent claims or support the source lacks.
- usage: "fix the grammar / settle the punctuation." A lightweight correctness-only pass (CAP-37). Settle grammar, punctuation, and disputed usage only; distinguish ungrammatical from merely ambiguous, and grammar from register. A contested "rule" is flagged for judgment, not silently enforced. A trivial correctness fix needs no full review-document pass; it changes no claim and holds the same strict fidelity.
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 · 198 lines · 191 tokens per session scan A ead2bbbf4e9b
revise-prose 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 191 tokens to every session and 2,524 once invoked, about $0.0010 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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