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CB interview-crash-coach

根据公司和岗位快速准备面试，适用于公司调研、岗位知识、面试题练习、 回答框架和逐题模拟面试反馈，无需上传简历；保存个人练习需另行同意。 / Prepare for a company-and-role interview with public research, role knowledge, practice questions, hypothetical answer frameworks, and interactive mock feedback. No resume is required. JishuDB retains the preparation pack; saving personal practice requires separate explicit approval.

ClawHub Agent Skills author: bowen-aijishu v0.1.7 MIT-0 9 files · 2 scripts body ≈ 5 063 tokens Open the sourceclawhub.ai↗ analyzed 8 d ago

根据公司和岗位快速准备面试，适用于公司调研、岗位知识、面试题练习、 回答框架和逐题模拟面试反馈，无需上传简历；保存个人练习需另行同意。 / Prepare for a company-and-role interview with public research, role knowledge, practice…

As a process B 78/100 · Nearly there — weak spots: result and completion

ProcedureAI and agentstype 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
C
89/100
safety, quality, tests
Safety 60%
99
Quality 40%
74
Run on models
none yet
Process rating
B
78/100
Nearly there
Result and completion w 14
0
When it triggers w 12
50
Execution cost w 6
70
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Secrets in code secret-high-entropy-token references/jishudb-setup/scripts/install-macos.sh:287
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    exactKeys(candidate.signing, ['certificateExpiresAt', 'cert…256', 'nativeFileCount'], 'candidate.signing');
    quoted

Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5063 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 78/100

  • 0Result and completion. Does not say what the result is
  • 50When it triggers. No condition that starts the skill
  • 70Execution cost. Instruction body is 5063 tokens
  • 100Tools and files. No external tools needed
  • 100Steps. 42 steps
  • 100Inputs and preconditions. Inputs and preconditions are listed
  • 100Failures and branches. 2 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress

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 354: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 42 items
  • +4Has examples (0 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: clean
This skill is coherent and disclosed, but users should understand that it can set up JishuDB Desktop before doing interview preparation.
LLM: benign (high) · VirusTotal: · 11 Oct 2026