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 DukeTwoCan/autonovel-agent-skills --skill autonovel-prose-reviewgit clone --depth 1 https://github.com/DukeTwoCan/autonovel-agent-skillsWrote 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/duketwocan/autonovel-agent-skills/autonovel-prose-review)<a href="https://agentmods.dev/skills/duketwocan/autonovel-agent-skills/autonovel-prose-review"><img src="https://agentmods.dev/badge/skills/duketwocan/autonovel-agent-skills/autonovel-prose-review/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/duketwocan/autonovel-agent-skills/autonovel-prose-review"><img src="https://agentmods.dev/badge/skills/duketwocan/autonovel-agent-skills/autonovel-prose-review.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 | $0.00117 | $0.01748 |
| Opus 5 | $0.00059 | $0.00874 |
| Sonnet 5 | $0.00023 | $0.00350 |
| Haiku 4.5 | $0.00012 | $0.00175 |
Grade A, and why
autonovel-prose-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Autonovel — Prose review (user-triggered, targeted)
Polish prose at the line level for a specific scope. Conversational — the agent suggests, the user decides.
When to use this skill
- User asks to "review chapter N", "polish the prose in ch X-Y", "look at the heist arc", "do a prose pass"
- User wants to iterate on prose quality with the agent rather than autopilot
- Never auto-invoked by the pipeline — user-driven only
Prerequisites
!`test -d "$AUTONOVEL_WORKSPACE/$NOVEL_SLUG/chapters" && ls "$AUTONOVEL_WORKSPACE/$NOVEL_SLUG/chapters" | head`
The novel needs at least one drafted chapter.
Workflow
Step 1 — Resolve scope
The user supplies a scope. Use references/scope-resolver.md to map natural-language scopes to chapter ranges:
"ch 7"→[7]"ch 7-10"→[7, 8, 9, 10]"chapters 7 through 10"→[7, 8, 9, 10]"act 2"→ look up act-to-chapter mapping inoutline.md"the heist arc"/"the romance subplot"→ searchoutline.mdheadings and arc summaries"all of part 1"→ look up part mapping inoutline.md"the last 3 chapters"→[N-2, N-1, N]fromstate.jsonchapters_drafted
If the scope is ambiguous, ask the user to clarify. Show your interpretation before proceeding.
Step 2 — Load context
Read:
- The chapter files in scope (full prose)
voice.md(target voice signature)references/anti-slop.md(from umbrella autonovel skill)references/prose-rubric.md(this skill)genre_context/story-contract.md(story-specific promises and required payoffs that line edits must preserve)genre_context/compiled/evaluation-chapter.md(selected-pack semantic guidance and guardrails)genre_context/resolved.json(selected pattern bundle for the mechanical rescore)
Budget check: ≤4 chapters at a time. If scope > 4 chapters, use lib/chunk_text.py to split into 4-chapter windows and process sequentially (with a fresh prose-review per window).
Assemble a current PROFILE REQUIREMENTS block for each review window using
the exact resolved chapter numbers in that window. The assembler reads
profile.rating and profile.content_tags from state.json, normalized tags
and literal exclusions from genre_context/resolved.json, the coverage map
from outline.md, and the matching rating definition from
../autonovel/references/ratings.md:
What ships with it
4 files 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.
- 12d ago First seen · 151 lines · 117 tokens per session scan A 2f7499e8f6dd
autonovel-prose-review is a skill published in the GitHub repository DukeTwoCan/autonovel-agent-skills (2 stars, last pushed 1mo ago), licensed MIT. It adds 117 tokens to every session and 1,748 once invoked, about $0.0006 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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