BC novel-factory
用初五小说工匠的完整流程创作爽文小说：聊个方向，自动生成完整创作提示词→大纲→卷级规划→逐章生成→九维审查→一键Word。内置记忆系统防吃书。独家含番茄小说合规红线+现实解谜写法+流量节点方法论（豆包seed终审实战沉淀）。反成功学定位：不是帮你写，是AI给你打工。 触发词：AI写小说、网文、小说生成。
用初五小说工匠的完整流程创作爽文小说：聊个方向，自动生成完整创作提示词→大纲→卷级规划→逐章生成→九维审查→一键Word。内置记忆系统防吃书。独家含番茄小说合规红线+现实解谜写法+流量节点方法论（豆包seed终审实战沉淀）。反成功学定位：不是帮你写，是AI给你打工。 触发词：AI写小说、网文、小说生成。
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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: 13. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "display_name" - note
frontmatter-keyunknown frontmatter key "display_name_en" - note
frontmatter-keyunknown frontmatter key "description_zh" - note
frontmatter-keyunknown frontmatter key "description_en"
Process rating: all ten parameters 53/100
- 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
- 100Tools and files. No external tools needed
- 100Steps. 86 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2931 tokens
- 100Running it twice. No mutating operations
- low 19 top-level sections: this looks like several domains in one skill
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
- -227 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 152: enough signal without eating the budget
- +4Structure: 64 headings
- +3Step-by-step instructions: 86 items
- +4Has examples (17 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.