BC investment-performance-review
围绕一定周期内招商引资工作的整体推进情况，系统梳理招商成果、签约项目、在谈项目、 落地进展、项目转化效率、招商渠道效果、产业匹配情况、存在问题短板及后续改进方向， 形成面向领导汇报、部门复盘、招商工作优化和下一阶段行动部署的招商成效复盘报告。 本技能核心解决"这一阶段招商工作做得怎么样、取得了哪些成果、哪些项目有实质进展、 哪些环节存在问题、后续应该如何优化招商策略和推进机制"等核心问题。 当用户需要总结招商成果、复盘招商工作成效、分析签约落地项目情况、评估项目转化效率、 梳理招商渠道效果、诊断招商工作短板、为领导汇报撰写招商复盘材料、制定下一阶段招商计划、 形成招商成效复盘报告时，激活此技能。
围绕一定周期内招商引资工作的整体推进情况，系统梳理招商成果、签约项目、在谈项目、 落地进展、项目转化效率、招商渠道效果、产业匹配情况、存在问题短板及后续改进方向， 形成面向领导汇报、部门复盘、招商工作优化和下一阶段行动部署的招商成效复盘报告。…
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: 2. 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 "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "summary" - note
frontmatter-keyunknown frontmatter key "triggers" - note
frontmatter-keyunknown frontmatter key "parameters" - note
frontmatter-keyunknown frontmatter key "tools"
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. 254 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1412 tokens
- 100Running it twice. No mutating operations
- low 17 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
- +4No input/output examples
- +2Single-language instructions
- +3Description length 301: enough signal without eating the budget
- +4Structure: 61 headings
- +3Step-by-step instructions: 254 items
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.