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-gradegit 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-grade)<a href="https://agentmods.dev/skills/duketwocan/autonovel-agent-skills/autonovel-grade"><img src="https://agentmods.dev/badge/skills/duketwocan/autonovel-agent-skills/autonovel-grade/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-grade"><img src="https://agentmods.dev/badge/skills/duketwocan/autonovel-agent-skills/autonovel-grade.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 | $0.00105 | $0.02360 |
| Opus 5 | $0.00053 | $0.01180 |
| Sonnet 5 | $0.00021 | $0.00472 |
| Haiku 4.5 | $0.00011 | $0.00236 |
Grade A, and why
autonovel-grade scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Autonovel — Grade (user-triggered, manual quality report)
Run every mechanical slop detector plus the sentence-grading pass over a scope and write a self-contained report. This skill is user-triggered only — it is never part of the autopilot path, never invoked or waited on by the pipeline, and never invoked by any other skill.
When to use this skill
- User says "grade chapter N", "grade the manuscript", "how sloppy is chapter N", or "give me a slop report"
- User is reviewing the
needs_attentionqueue in state.json (populated by the drafting skill's surgical-rewrite stall rule — seeautonovel-drafting/references/retry-policy.md) and wants a detailed report on the flagged chapters before deciding whether to fix them by hand or hand them to a stronger model - Never invoked automatically — this skill only runs when the user asks for it directly
Prerequisites
!`test -d "$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: a chapter, a range, or "manuscript" for everything. Use autonovel-prose-review/references/scope-resolver.md (reference it, don't duplicate its logic) to map natural-language scopes to chapter ranges. If the scope is ambiguous, ask the user to clarify and show your interpretation before proceeding.
Step 2 — Check state.json for needs_attention
Read $AUTONOVEL_WORKSPACE/$NOVEL_SLUG/state.json. If needs_attention is non-empty:
- Any entry with a
chapternumber that falls inside the resolved scope must be covered in the report regardless of how it scores mechanically — call it out explicitly in the summary. - An entry with
"chapter": nullis a systemic pattern note (3+ consecutive chapters stalled during drafting). Surface itsnotetext verbatim at the top of the report's Summary section — it usually points at an outline or foundation problem, not chapter-level slop, and the user needs to see it before reading chapter-level findings. - If the user's scope doesn't include a flagged chapter but
needs_attentionhas entries, mention their existence and chapter numbers in passing so the user can re-run with a wider scope.
What ships with it
7 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 · 158 lines · 105 tokens per session scan A cfa218432310
autonovel-grade is a skill published in the GitHub repository DukeTwoCan/autonovel-agent-skills (2 stars, last pushed 1mo ago), licensed MIT. It adds 105 tokens to every session and 2,360 once invoked, about $0.0005 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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