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BF visit-analyzer

拜访记录分析引擎。根据员工的拜访沟通记录，AI 分析销售阶段、跟进策略、客户洞察、承诺事项和风险预估。当员工要求查看某个客户/公司的聊天分析时触发，自动生成项目画像并输出 H5 链接。

ClawHub Agent Skills author: vivalavida-say-hi v1.0.0 MIT-0 2 files body ≈ 8 158 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

拜访记录分析引擎。根据员工的拜访沟通记录，AI 分析销售阶段、跟进策略、客户洞察、承诺事项和风险预估。当员工要求查看某个客户/公司的聊天分析时触发，自动生成项目画像并输出 H5 链接。

As a process F 34/100 · Will not run — References files that are not bundled: {h5_url}

AnalyzerSales and CRMtype 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
79/100
safety, quality, tests
Safety 60%
99
Quality 40%
48
Run on models
none yet
Process rating
F
34/100
Will not run
References files that are not bundled: {h5_url}
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 SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  3. 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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Secrets in code secret-high-entropy-token SKILL.md:443
    High-entropy token-like string (may be an id, hash or a credential)
    8bc1…929_CRM方案价格相对比及商务谈判进展.md

Files scanned: 2. 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 body-long SKILL.md body ≈ 8158 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: {h5_url}
  • note frontmatter-key unknown frontmatter key "triggers"

Process rating: all ten parameters 34/100

Will not run. References files that are not bundled: {h5_url}
  • 0Tools and files. 1 referenced file(s) missing: {h5_url}
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 2 mutating operations with no state check
  • 40Execution cost. Instruction body is 8158 tokens: crowds the task out of the window
  • 50Failures and branches. 0 branches, has a failure section
  • 100Steps. 31 steps
  • 100Consistency. Name and required fields are in place
  • low 13 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)
  • +3Description length 92: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • +1No license
  • +2Single-language instructions
  • +4Structure: 53 headings
  • +3Step-by-step instructions: 31 items
  • +4Has examples (33 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 48.

External checks

ClawHub: suspicious
This skill has a coherent visit-analysis purpose, but it handles employee passwords and private communication records in ways users should review carefully before installing.
LLM: suspicious (high) · VirusTotal: · 15 Jun 2026