AB industry-deep-dive-pipeline
This skill should be used when turning a topic brief, research materials, vendor case, policy event, or industry question into a publish-ready single deep-dive article for technology, AI, data, cloud, or enterprise-software audiences. It runs source verification, originality and competition review, full editorial planning, two human decision gates, drafting, deterministic red-line checks, an existing eight-role review panel, revision, and final evidence packaging. It stops at an approved Markdown article plus evidence and review records; it does not create publication layouts, covers, social copy, CMS drafts, or publish content. 【适用】中立第三方产业深度研究 / 行业长文（个人 IP、公众号深度稿、厂商案例的独立分析）。【不适用】品牌营销稿、产品稿、按 content brief 写的推广文、技术教程——这类内容请用对应项目工作区里专门的写作 Skill；本 Skill 不做品牌露出与营销措辞，也不产出发布物料。
This skill should be used when turning a topic brief, research materials, vendor case, policy event, or industry question into a publish-ready single…
As a process B 78/100 · Nearly there — weak spots: progress reporting
How to improve
- 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
- note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "not_for" - note
frontmatter-keyunknown frontmatter key "description_zh" - note
frontmatter-keyunknown frontmatter key "description_en" - note
frontmatter-keyunknown frontmatter key "agent_created" - note
frontmatter-keyunknown frontmatter key "read_when"
Process rating: all ten parameters 78/100
- 0Progress reporting. Says nothing while it works
- 50When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 60Result and completion. Output format stated, no completion criterion
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Tools and files. No external tools needed
- 100Steps. 82 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1259 tokens
- 100Running it twice. No mutating operations
- low 10 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)
- +1No license
- +2Single-language instructions
- +3Description length 782: enough signal without eating the budget
- +4Structure: 23 headings
- +3Step-by-step instructions: 82 items
- +3Output format is stated explicitly
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.