SKILLEMALL.ai
GitHub ↗ RU Sign in

BF ccai-conversation-analysis

该技能调用阿里云晓蜜 CCAI AIO，对客服通话或文字对话进行 AI 智能分析，支持摘要生成、服务质检、情绪检测、满意度评估、关键词提取、字段抽取、QA 生成、用户画像、标签分类等多种分析任务，输入可以是文本对话或语音文件 URL。 当用户问题涉及「总结/摘要一段对话或通话内容」「对客服录音做质检或合规检查」「分析用户情绪或满意度」「从对话中提取关键词、字段、待办事项」「对通话做 QA 抽取或用户画像」时使用该技能。

ClawHub Agent Skills author: yuya-xyf v1.0.0 MIT-0 6 files body ≈ 887 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process F 31/100 · Will not run — References files that are not bundled: references/scenarios.md

AnalyzerInfrastructuretype 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
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
70
Run on models
none yet
Process rating
F
31/100
Will not run
References files that are not bundled: references/scenarios.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: 6. 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/scenarios.md

Process rating: all ten parameters 31/100

Will not run. References files that are not bundled: references/scenarios.md
  • 0Tools and files. 1 referenced file(s) missing: references/scenarios.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 (ccai-conversation-analysis) differs from the folder (intelligent-conversation-analysis)
  • 100Steps. 49 steps
  • 100Execution cost. Instruction body is 887 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 211: enough signal without eating the budget
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 49 items
  • +4Has examples (6 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)

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

External checks

ClawHub: suspicious
The skill performs the advertised Alibaba Cloud conversation analysis, but it needs review because it can use local cloud credentials, sends sensitive conversations to a third party, and documents an under-bounded background polling flow.
LLM: suspicious (high) · VirusTotal: · 29 May 2026