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百万字小说写作引擎——把长篇写作变成事务性写作。AI 每写一章提交一个语义事务（正文+状态变更），门禁逐条复核（禁区/伏笔状态机/正文对照）后才落盘。角色不会突然用上他不知道的信息，物品不会凭空易主，伏笔不会收了又埋。新会话秒恢复：state 一条命令拿到全部世界状态。当需要写长篇小说、续写长篇、维护小说世界观一致性、管理伏笔/人物状态/时间线时使用。

ClawHub Agent Skills author: dongsheng123132 v1.1.1 MIT-0 3 files body ≈ 626 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

百万字小说写作引擎——把长篇写作变成事务性写作。AI 每写一章提交一个语义事务（正文+状态变更），门禁逐条复核（禁区/伏笔状态机/正文对照）后才落盘。角色不会突然用上他不知道的信息，物品不会凭空易主，伏笔不会收了又埋。新会话秒恢复：state…

As a process C 50/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorSoftware developmentWriting and documentsAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
70
Run on models
none yet
Process rating
C
50/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "summary"

Process rating: all ten parameters 50/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 75Steps. 3 steps
  • 100Tools and files. No external tools needed
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 626 tokens
  • 100Running it twice. No mutating operations

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +3Description length 177: enough signal without eating the budget
  • +4Structure: 7 headings
  • +3Step-by-step instructions: 3 items
  • +4Has examples (5 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 70.

External checks

ClawHub: clean
This skill is a disclosed local writing workflow that persists novel state files and does not show hidden or unrelated high-risk behavior.
LLM: benign (high) · VirusTotal: · 2 Sept 2026