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-draftinggit 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-drafting)<a href="https://agentmods.dev/skills/duketwocan/autonovel-agent-skills/autonovel-drafting"><img src="https://agentmods.dev/badge/skills/duketwocan/autonovel-agent-skills/autonovel-drafting/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-drafting"><img src="https://agentmods.dev/badge/skills/duketwocan/autonovel-agent-skills/autonovel-drafting.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 | $0.00098 | $0.02935 |
| Opus 5.5 | $0.00039 | $0.01174 |
| Sonnet 5.5 | $0.00020 | $0.00587 |
| Haiku 4.5 | $0.00010 | $0.00294 |
Grade A, and why
autonovel-drafting scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 237 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Autonovel — Phase 2 (Drafting)
Draft each chapter in sequence from the scene-level outline. Per-chapter loop: draft → mechanical gates → surgical rewrite loop → grading gate (see references/surgical-rewrite.md).
When to use this skill
- State.json shows
"phase": "drafting" - Foundation complete; outline.md has scene-level beats; world/characters/voice/canon all present
chapters_drafted < chapters_total(or chapters_total is 0 and we need to count from outline)
Prerequisites
!`cd "$AUTONOVEL_WORKSPACE/$NOVEL_SLUG" && ls -la outline.md world.md characters.md voice.md canon.md`
!`cat "$AUTONOVEL_WORKSPACE/$NOVEL_SLUG/state.json"`
If any foundation file is missing, hand back to autonovel-foundation.
Workflow
Step 1 — Resolve the next chapter
Read chapters_drafted + 1 as the next chapter number. New foundations already
carry chapters_total. For a legacy drafting state where it is zero, count the
validated outline headings for the loop bound; the first atomic checkpoint
persists that derived count. Do not edit state.json by hand.
Step 2 — Draft loop
For each chapter index N from chapters_drafted + 1 to chapters_total:
a. Compile and build context for chapter N. At the start of every chapter, run the deterministic preflight before spending a model call:
python ${HERMES_SKILL_DIR}/lib/validation.py preflight "$AUTONOVEL_WORKSPACE/$NOVEL_SLUG" --chapter N
Nonzero exit means the accepted foundation does not contain a safe drafting packet for this chapter. Report the returned issue codes and stop this chapter; the command does not mutate state. After preflight, re-run the task-specific resolver (unchanged inputs use its fingerprint cache):
python ${HERMES_SKILL_DIR}/../autonovel/lib/genre_resolver.py compile --state "$AUTONOVEL_WORKSPACE/$NOVEL_SLUG/state.json" --workspace "$AUTONOVEL_WORKSPACE/$NOVEL_SLUG" --task drafting.chapter
Read:
outline.md— get the scene-beat section for chapter Nworld.md,characters.md,voice.md,canon.md— fullchapters/ch_{N-1:02d}.mdif N > 1 — get the last 1000 words for continuity (prose texture and immediate scene state; NOT a source of facts — see the STORY STATE block below, which replaces re-reading older chapters for facts)references/chapter-prompt.md(THIS SKILL's reference dir) — get the chapter draft templategenre_context/story-contract.md— the persistent story-specific genre promisesgenre_context/compiled/drafting.md— the bounded static drafting packetgenre_context/compiled/evaluation-chapter.md— the profile-compliance and semantic genre-slop criteria used by Gate 4genre_context/resolved.json— selected-pack metadata and the generated pattern-bundle pointer used by the mechanical scanprofilefrom state.json — rating, exclusions, and content tags to match against the outline coverage map; do not reopen source pack Markdown from Drafting- STORY STATE block (if
story_state/facts.jsonexists — see references/fact-extraction.md for how it's populated):!`python3 ${HERMES_SKILL_DIR}/lib/story_state.py query "$AUTONOVEL_WORKSPACE/$NOVEL_SLUG/story_state/facts.json" {N} <characters-in-this-beat>`<characters-in-this-beat>= the entity keys of characters named in chapter N's outline beat (space-separated CLI args). Include the returned facts and participating characters in{GENRE_DRAFTING_BLOCK}rather than duplicating a separate story-state block. Budget: this story-state portion must stay <= 1.5k tokens; this cap does not include or truncate the story contract or compiled drafting packet. If the query runs longer, narrow the subject list further to only the characters actually on-page in this beat rather than the full cast. Ifstory_state/facts.jsondoes not exist yet, skip this block — it is created on the first chapter's fact-extraction step (references/fact-extraction.md).
What ships with it
15 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.
- lib/chapter_patch.py 6.8 KB runs code
- lib/genre_models.py 3.0 KB runs code
- lib/genre_patterns.py 12 KB runs code
- lib/grading.py 2.7 KB runs code
- lib/slop_detect.py 20 KB runs code
- lib/slop_ngrams.py 8.8 KB runs code
- lib/state.py 3.2 KB runs code
- lib/story_state.py 10 KB runs code
- lib/validation.py 31 KB runs code
- references/chapter-prompt.md 4.1 KB
- references/fact-extraction.md 8.4 KB
- references/quality-rubric.md 4.6 KB
- references/retry-policy.md 1.5 KB
- references/sentence-grading.md 1.9 KB
- references/surgical-rewrite.md 9.7 KB
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.
- 2mo ago First seen · 237 lines · 98 tokens per session scan A 164926171886
autonovel-drafting is a skill published in the GitHub repository DukeTwoCan/autonovel-agent-skills (2 stars, last pushed 3mo ago), licensed MIT. It adds 98 tokens to every session and 2,935 once invoked, about $0.0004 per session on Opus 5.5. 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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