CD career-planning
求职全链路。当用户涉及职业规划（就业形势研判/求职迷茫/转行/路径/能力补齐/复盘，及职业定位/就业选择/跳槽分析/创业建议四类职业决策）、岗位分析（JD 拆解/岗位值不值得投/匹配度）、简历优化（梳理/亮点/针对 JD 改写）、面试准备（押题/模拟/回答结构）、投递优化（节奏/排序/版本管理/复盘）、HR 面与谈薪（筛选逻辑/表达/薪酬沟通/offer 比较）任一求职意图时使用。主文件负责模块路由：判定用户意图 → 加载对应 references/module-*.md 执行规范。内置默认画像（普通本科 / 0–3 年经验 / 薪资高增长快 / AI 应用、新能源储能电控、工业机器人、半导体、网络安全五大赛道），用户输入可逐项覆盖；调研支持联网与降级知识库；人岗匹配与选岗推荐衔接 jd-resume-matcher / resume-job-match。
求职全链路。当用户涉及职业规划（就业形势研判/求职迷茫/转行/路径/能力补齐/复盘，及职业定位/就业选择/跳槽分析/创业建议四类职业决策）、岗位分析（JD 拆解/岗位值不值得投/匹配度）、简历优化（梳理/亮点/针对 JD 改写）、面试准备（押题/模拟/回答结构）、投递优化（节奏/排序/版本管理/复盘）、HR…
As a process D 35/100 · Unfinished process — References files that are not bundled: references/module-*.md
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
- 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: 14. 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") - warning
missing-refreference to a missing file: references/module-*.md - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "summary"
Process rating: all ten parameters 35/100
- 0Tools and files. 1 referenced file(s) missing: references/module-*.md
- 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
- 100Steps. 43 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1721 tokens
- 100Running it twice. No mutating operations
- low 12 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
- -212 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 383: enough signal without eating the budget
- +4Structure: 15 headings
- +3Step-by-step instructions: 43 items
- +4Reference files are cited in the instructions (11 of 11)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 61.