BD resume-jd-review
校招/实习互联网产品经理简历评分与面试模拟技能。当用户需要按《校招产品经理能力评价体系》对简历评分、优化简历，或基于 JD 生成模拟面试题时应使用此技能。支持简历图片/PDF（腾讯云 OCR）或纯文本输入，输出评分报告（5 维度：经验匹配20%/逻辑30%/表达20%/AI探索15%/素养15%）、优化后简历与 7 大类面试题，零大模型依赖、得分可追溯。
校招/实习互联网产品经理简历评分与面试模拟技能。当用户需要按《校招产品经理能力评价体系》对简历评分、优化简历，或基于 JD 生成模拟面试题时应使用此技能。支持简历图片/PDF（腾讯云 OCR）或纯文本输入，输出评分报告（5 维度：经验匹配20%/逻辑30%/表达20%/AI探索15%/素养15%）、优化后简历与 7…
As a process D 41/100 · Unfinished process — 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: 27. 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 4, column 17: description_en: Resume scoring & interview prep for campus/intern PM roles: rul… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "description_zh" - note
frontmatter-keyunknown frontmatter key "description_en"
Process rating: all ten parameters 41/100
- 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
- 40Consistency. Frontmatter name (resume-jd-review) differs from the folder (campus-pm-coach)
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 22 steps
- 100Execution cost. Instruction body is 981 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)
- +3Output format is not stated: the model decides each time
- -33 of 11 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 178: enough signal without eating the budget
- +4Structure: 11 headings
- +3Step-by-step instructions: 22 items
- +4Has examples (2 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 57.