SKILLEMALL.ai

AC zh-novel-writer

批量生成网络小说章节。通过环境变读取 API keys 并调用外部 LLM API (ModelScope, Fyra, Ph8) 生成中文小说内容。 使用场景:用户给出大纲并要求"批量生成章节"、"写第X章到第Y章"、"后台静默写作"。 前置要求:需设置环境变量 NOVEL_MODELSCOPE_KEY 或 NOVEL_FYRA_KEY 或 NOVEL_PH8_KEY 至少一个。 外部依赖:Python 3, pip install httpx。 NOT for: 单章精修、人工审稿、出版级校对。

ClawHub Agent Skills author: Shine8592 v1.0.3 MIT-0 5 files body ≈ 246 tokens Open the sourceclawhub.ai analyzed 3 d ago

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

IntegrationAI and agentsInfrastructureSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
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: 5. 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")

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
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 11 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 246 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

  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 3 example trigger phrases
  • +4Description says when NOT to use the skill
  • +3Description length 252: enough signal without eating the budget
  • +4Structure: 7 headings
  • +3Step-by-step instructions: 11 items
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

External checks

ClawHub: clean
This skill is a disclosed batch novel-writing helper that sends user-provided outline and chapter context to named LLM APIs and saves generated chapters locally.
LLM: benign (high) · VirusTotal: · 29 May 2026