BC research-article-crafter
研究文章匠人辅助撰写高质量、有深度、有据可查的长篇内容,核心功能包括选题研究(关键词研究+资料搜集+来源分层)、结构设计(大纲+钩子+段落分配)、分段撰写与反馈(引用嵌入+分段反馈+过渡衔接)、钩子标题优化与全文校审(事实核查+逻辑审查+语言润色)。适用于技术博客、行业分析、白皮书、研究报告、深度评测场景。触发关键词:内容写作、文章撰写、深度文章、研究写作、长文创作、技术博客、白皮书、行业分析、内容创作、文章优化。 功能涵盖: research, article, crafter。
研究文章匠人辅助撰写高质量、有深度、有据可查的长篇内容…
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.
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- 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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 8, column 14: description: 研究文章匠人辅助撰写高质量、有深度、有据可查的长篇内容,核心功能包括选题研究(关键词研究+资料搜集+来源分层)、结构设计(大纲+钩子… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
description-long-hermesdescription is 243 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - warning
description-no-whenneither description nor a "## When to Use" section says when to use the skill - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "summary" - note
frontmatter-keyunknown frontmatter key "summary_zh" - note
frontmatter-keyunknown frontmatter key "tools" - note
frontmatter-keyunknown frontmatter key "pricing_tier"
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. Tools declared in frontmatter
- 100Steps. 65 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1984 tokens
- 100Running it twice. No mutating operations
- low 24 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
- +2Single-language instructions
- +3Description length 243: enough signal without eating the budget
- +4Structure: 48 headings
- +3Step-by-step instructions: 65 items
- +4Has examples (2 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 54.