AC patent-panorama-analysis
专利技术全景分析报告自动生成。用户上传专利数据Excel表格（含标题、申请人、申请日、法律状态、受理局、被引次数等字段）和技术拆解Excel表格后，自动分析专利数据并生成可编辑的HTML全景分析报告。 报告包含5大模块：技术概况分析、重点技术分支分析、竞争对手分析、专利风险分析、企业专利布局建议。 触发条件：当用户提及"专利分析""技术全景分析""专利全景报告""专利布局分析""CMC专利分析""专利竞争分析""专利风险""FTO分析""技术分解""专利趋势"等关键词时自动触发。也适用于用户上传专利数据Excel并要求生成分析报告的场景。
专利技术全景分析报告自动生成。用户上传专利数据Excel表格（含标题、申请人、申请日、法律状态、受理局、被引次数等字段）和技术拆解Excel表格后，自动分析专利数据并生成可编辑的HTML全景分析报告。 报告包含5大模块：技术概况分析、重点技术分支分析、竞争对手分析、专利风险分析、企业专利布局建议。…
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: 6. 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 "copyright"
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. 35 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 937 tokens
- 100Running it twice. No mutating operations
- low The response is described with custom markup (3 tags): a typed call is more reliable
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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 5 example trigger phrases
- +3Description length 272: enough signal without eating the budget
- +4Structure: 15 headings
- +3Step-by-step instructions: 35 items
- +4Has examples (6 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.