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WhoBot (呼波特) AI电话数字员工知识库。加载后可回答关于 WhoBot 的一切问题：公司信息、产品能力、核心技术（拟人化引擎 & 拟角色飞轮）、业务场景、行业案例、团队、合规等。 触发条件：用户提问涉及 WhoBot、呼波特、AI电话数字员工、AI通话、智能电话、电话机器人、语音AI、拟人化引擎、拟角色、WhoBot产品/技术/团队/融资/行业方案等相关话题。 Trigger when: user asks about WhoBot, 呼波特, AI phone digital employee, voice AI, humanization engine, role-play flywheel, or any WhoBot-related topics.

ClawHub Agent Skills author: WhoBot AI v1.0.0 MIT-0 5 files body ≈ 252 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 37/100 · Will not run — References files that are not bundled: scripts/sync-knowledge.sh

ProcedureInfrastructuretype 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
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
Run on models
none yet
Process rating
F
37/100
Will not run
References files that are not bundled: scripts/sync-knowledge.sh
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. 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: 5. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: scripts/sync-knowledge.sh

Process rating: all ten parameters 37/100

Will not run. References files that are not bundled: scripts/sync-knowledge.sh
  • 0Tools and files. 1 referenced file(s) missing: scripts/sync-knowledge.sh
  • 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
  • 40Consistency. Frontmatter name (openclaw-whobot) differs from the folder (openclaw-whobot-skill)
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 18 steps
  • 100Execution cost. Instruction body is 252 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
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +3Description length 337: enough signal without eating the budget
  • +4Structure: 3 headings
  • +3Step-by-step instructions: 18 items
  • +4Reference files are cited in the instructions (1 of 1)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

External checks

ClawHub: clean
This is a WhoBot product knowledge skill with a local MCP query server, and the reviewed files do not show hidden data access, credential use, persistence, or destructive behavior.
LLM: benign (high) · VirusTotal: · 29 May 2026