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BF job-prep-kit

求职准备三段链路 Skill。用户只需提供简历（PDF/Word/文本）+ 目标公司 + 岗位 + JD，自动完成：① 岗位调研（面试风格、核心能力、隐性门槛、最新动态）② 简历改写（按岗位语言翻译真实经历，输出统一排版的 .docx）③ 面试准备（基于改后简历反推考点、自我介绍、逐题话术）。触发场景：求职、改简历、准备面试、申请实习/校招/社招、按 JD 改简历、投前准备、面试冲刺等。

ClawHub Agent Skills author: qingjiu061 v1.0.0 MIT-0 9 files body ≈ 1 265 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

求职准备三段链路 Skill。用户只需提供简历（PDF/Word/文本）+ 目标公司 + 岗位 + JD，自动完成：① 岗位调研（面试风格、核心能力、隐性门槛、最新动态）② 简历改写（按岗位语言翻译真实经历，输出统一排版的 .docx）③…

As a process F 31/100 · Will not run — References files that are not bundled: references/resume-playbook.md, scripts/generate_resume.py, references/interview-playbook.md

ProcedureWordWriting and documentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
59
Run on models
none yet
Process rating
F
31/100
Will not run
References files that are not bundled: references/resume-playbook.md, scripts/generate_resume.py, references/interview-playbook.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The text references files that are not there: add them or drop the references.
For the model run — optional
  • 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: 9. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: references/resume-playbook.md
  • warning missing-ref reference to a missing file: scripts/generate_resume.py
  • warning missing-ref reference to a missing file: references/interview-playbook.md
  • warning missing-ref reference to a missing file: scripts/sample_resume.json
  • warning missing-ref reference to a missing file: examples/sample_resume.json
  • warning missing-ref reference to a missing file: examples/README.md
  • note frontmatter-key unknown frontmatter key "agent_created"

Process rating: all ten parameters 31/100

Will not run. References files that are not bundled: references/resume-playbook.md, scripts/generate_resume.py, references/interview-playbook.md
  • 0Tools and files. 6 referenced file(s) missing: references/resume-playbook.md, scripts/generate_resume.py, references/interview-playbook.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
  • 40Consistency. Frontmatter name (job-prep-kit) differs from the folder (resumeskill)
  • 100Steps. 64 steps
  • 100Execution cost. Instruction body is 1265 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 195: enough signal without eating the budget
  • +4Structure: 27 headings
  • +3Step-by-step instructions: 64 items
  • +4Has examples (6 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 59.

External checks

ClawHub: clean
This skill is a disclosed resume and interview preparation helper, with no evidence of hidden data access, credential use, persistence, or destructive behavior.
LLM: benign (high) · VirusTotal: · 14 Aug 2026