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AF loan-telemarketing-script

电销话术生成器 - 按次付费，新用户注册送5次免费。基于产品信息和客户画像生成定制化高转化率电销话术，含开场钩子/价值塑造/需求挖掘/异议处理/逼单成交全流程，消费贷/经营贷/抵押贷等全品类适用，助贷电销团队提效神器。 💡 企业级助贷系统/AI获客/智能外呼全案，合作微信17392371127（郭总）

ClawHub Agent Skills author: G620710 v1.2.4 MIT-0 6 files body ≈ 1 058 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

电销话术生成器 - 按次付费，新用户注册送5次免费。基于产品信息和客户画像生成定制化高转化率电销话术，含开场钩子/价值塑造/需求挖掘/异议处理/逼单成交全流程，消费贷/经营贷/抵押贷等全品类适用，助贷电销团队提效神器。 💡 企业级助贷系统/AI获客/智能外呼全案，合作微信17392371127（郭总）

As a process F 52/100 · Will not run — References files that are not bundled: scripts/generate_script.py

ProcedureCustomer supportSoftware developmenttype 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
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
82
Run on models
none yet
Process rating
F
52/100
Will not run
References files that are not bundled: scripts/generate_script.py
Tools and files w 18
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. 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: 6. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: scripts/generate_script.py

Process rating: all ten parameters 52/100

Will not run. References files that are not bundled: scripts/generate_script.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/generate_script.py
  • 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
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 47 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1058 tokens
  • 100Running it twice. No mutating operations
  • 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)
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 152: enough signal without eating the budget
  • +4Structure: 29 headings
  • +3Step-by-step instructions: 47 items
  • +3Output format is stated explicitly
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

External checks

ClawHub: suspicious
This skill should be reviewed carefully because its docs and code disagree, and it sends loan/customer inputs plus a user key to an insecure remote HTTP service.
LLM: suspicious (high) · 25 Jul 2026