BC human-writing-skills
Advanced multilingual AI humanizer for natural rewriting, fiction editing, long-form audit and continuity, verified chunked agent review, translationese review, and character consistency. Humanize AI text, remove robotic tone, edit fiction and novels, continue webnovel chapters, proofread writing, and audit story continuity, character voice, dialogue register and performance, scene geography, relationships, numbers, citations, source meaning, and translated-text fidelity. Use for AI writing cleanup, supplied-sample style matching, long-context fiction, essays, news, official, academic, legal, and technical prose. Trigger on humanize AI text, de-AI writing, natural rewriting, novel writing assistant, story consistency checker, scene ending audit, reflective ending, chunked audit, long-form agent audit, translationese audit, style consistency review, character consistency audit, dialogue audit, dialogue action audit, 增强版去 AI 写作 Skill、高级 AI 写作工具、去AI味、去AI写作、消除AI腔、AI人性化改写、AI文本润色、AI文章润色、小说润色、小说续写、AI式结尾、生硬结尾审查、无意义升华、长文一致性、长篇审查、分块审查、文风统一、统一文风、人物设定统一、人物一致性审查、跨章一致性、小说审查、报告审查、人物口吻、人物对白审查、对话生硬、对白动作、方言语域、翻译腔、翻译审查、战力设定、场景空间审查.
Advanced multilingual AI humanizer for natural rewriting, fiction editing, long-form audit and continuity, verified chunked agent review, translationese…
As a process C 52/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches
How to improve
- Shorten the description to 1024 characters.
- 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: 80. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
description-longdescription is 1130 chars, limit 1024
Process rating: all ten parameters 52/100
- 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
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 17 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1883 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)
- +3Description length 1130: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -31 of 1 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +4Structure: 5 headings
- +3Step-by-step instructions: 17 items
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (2 of 26)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 58.