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BF audio-analyzer

All-in-one audio analysis: transcribe, identify speakers by voiceprint, auto-detect scene (meeting/interview/training/talk), generate structured notes. The ONLY skill with persistent voice profile matching across sessions. 录音分析全流程：转写+说话人声纹识别+场景自动判断+结构化纪要。 唯一支持跨录音声纹档案匹配的 skill。支持 AssemblyAI / Whisper / Gemini 多引擎。

ClawHub Agent Skills author: JoJowillwater v1.2.1 MIT-0 12 files body ≈ 1 615 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 50/100 · Will not run — References files that are not bundled: references/voice-db.json

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
81/100
safety, quality, tests
Safety 60%
88
Quality 40%
70
Run on models
none yet
Process rating
F
50/100
Will not run
References files that are not bundled: references/voice-db.json
Tools and files w 18
0
Result and completion w 14
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Exfiltration medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

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 · 8

✓ No critical or high findings

Medium and low: 8
  • medium Exfiltration net-redirectable-api-key scripts/analyze.js:12
    Helper sends the API key to a host configured by an environment variable — the key can be redirected to another server
    API key + configurable base URL from environment
  • low Secrets in code secret-high-entropy-token scripts/package-lock.json:38
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…ibj+tODHI5/+l06Au2Pcriv/Gmet…weg==",
    detector
  • low Secrets in code secret-high-entropy-token scripts/package-lock.json:50
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…8fQ+wE2m…hIQ==",
    detector
  • low Secrets in code secret-high-entropy-token scripts/package-lock.json:74
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…9dM/mwVgvbZJaSNaRk+bshk…Kbz+IoId…W0Q==",
    detector
  • low Secrets in code secret-high-entropy-token scripts/package-lock.json:93
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…SDq+2kAA…MOe/+5cdoEdg==",
    detector
  • low Secrets in code secret-high-entropy-token scripts/package-lock.json:140
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…FrF+LTRo…W3g==",
    detector
  • low Exfiltration read-dotenv SKILL.md:76
    Reads a .env file
    cp .env.example .env
  • low Exfiltration read-dotenv SKILL.md:95
    Reads a .env file
    cp .env.example .env

Files scanned: 12. 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/voice-db.json
  • note frontmatter-key unknown frontmatter key "displayName"

Process rating: all ten parameters 50/100

Will not run. References files that are not bundled: references/voice-db.json
  • 0Tools and files. 1 referenced file(s) missing: references/voice-db.json
  • 0Result and completion. Does not say what the result is
  • 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
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 28 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1615 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 10 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
  • -214 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 314: enough signal without eating the budget
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 28 items
  • +4Has examples (8 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +3All 2 scripts are documented

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

External checks

ClawHub: suspicious
This is a coherent audio transcription and speaker-identification skill, but it handles very sensitive recordings, uploads audio or transcripts to cloud providers when configured, stores voice identifiers locally, and has a local Whisper command-execution risk with untrusted filenames.
LLM: suspicious (high) · VirusTotal: · 29 May 2026