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BF ai-coach-batch-session-summary

批量分析录音转写，生成多维度拓客分析报告。触发词：录音分析、 总结、音频总结、拜访记录总结。 当用户提到「分析录音」「看看录音数据」「最近的录音」「通话记录」且意图是批量统计/分析时触发。 注意：单独出现「录音」「拜访」时需结合上下文判断，若用户只是查看单条录音详情则不触发本技能。

ClawHub Agent Skills author: LegionSpace-Hackathon v1.1.1 MIT-0 16 files body ≈ 3 545 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 33/100 · Will not run — References files that are not bundled: ../fetch-legionclaw-invite-code/SKILL.md, ../openclaw-file-share/SKILL.md, URL

ProcedureInfrastructureWriting and documentstype 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
82/100
safety, quality, tests
Safety 60%
99
Quality 40%
57
Run on models
none yet
Process rating
F
33/100
Will not run
References files that are not bundled: ../fetch-legionclaw-invite-code/SKILL.md, ../openclaw-file-share/SKILL.md, 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 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 test-output/asr_completed_live.json:1
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    {"code":0,"data":{"endTime":"2026…:59","orgId":null,"records":[{"aiJiaolianResultJson":"{\"task_id\":\"f376…1a3\",\"workflow_run_id\":\"55b4…f-9
    quoted

Files scanned: 16. 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: ../fetch-legionclaw-invite-code/SKILL.md
  • warning missing-ref reference to a missing file: ../openclaw-file-share/SKILL.md
  • warning missing-ref reference to a missing file: URL

Process rating: all ten parameters 33/100

Will not run. References files that are not bundled: ../fetch-legionclaw-invite-code/SKILL.md, ../openclaw-file-share/SKILL.md, URL
  • 0Tools and files. 3 referenced file(s) missing: ../fetch-legionclaw-invite-code/SKILL.md, ../openclaw-file-share/SKILL.md, URL
  • 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
  • 30Running it twice. 1 mutating operations with no state check
  • 100Steps. 60 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3545 tokens
  • low 11 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)
  • +3Output format is not stated: the model decides each time
  • -31 of 2 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 141: enough signal without eating the budget
  • +4Structure: 30 headings
  • +3Step-by-step instructions: 60 items
  • +4Has examples (16 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 57.

External checks

ClawHub: suspicious
This skill mostly does what it says, but it handles sensitive call transcripts and publishes generated reports in ways that need careful review before installation.
LLM: suspicious (high) · 8 Jul 2026