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CF voice-agent

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ClawHub Agent Skills author: Wesley Armando v1.0.0 MIT-0 6 files body ≈ 5 562 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 24/100 · Will not run — weak spots: steps, result and completion, when it triggers

ProcedureInfrastructureAI and agentstype 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
C
61/100
safety, quality, tests
Safety 60%
75
Quality 40%
39
Run on models
none yet
Process rating
F
24/100
Will not run
Steps w 15
0
Result and completion w 14
0
When it triggers w 12
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 SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 5

✓ No critical or high findings

Medium and low: 5
  • medium Exfiltration net-credential-use SKILL.md:270
    Credential used in a network call (verify the destination is the intended service)
    curl -s https://api.elevenlabs.io/v1/user   -H "xi-api-key: $ELEVENLABS_API_KEY" | python3 -m json.tool
  • medium Exfiltration net-credential-use SKILL.md:313
    Credential used in a network call (verify the destination is the intended service)
    curl -X POST https://api.elevenlabs.io/v1/voices/add   -H "xi-api-key: $ELEVENLABS_API_KEY"   -F "name=Wesley"   -F "description=Wesley Armando principal voice"   -F "files=@/workspace/voice/samples/s
  • medium Exfiltration net-credential-use SKILL.md:319
    Credential used in a network call (verify the destination is the intended service)
    VOICE_ID=$(curl -s -X POST https://api.elevenlabs.io/v1/voices/add   -H "xi-api-key: $ELEVENLABS_API_KEY"   -F "name=Wesley"   -F "files=@/workspace/voice/samples/samp…mp3"   -F "files=@/workspac
  • medium Exfiltration net-credential-use SKILL.md:332
    Credential used in a network call (verify the destination is the intended service)
    curl -s https://api.elevenlabs.io/v1/voices   -H "xi-api-key: $ELEVENLABS_API_KEY"   | python3 -c "
  • medium Exfiltration net-credential-use SKILL.md:479
    Credential used in a network call (verify the destination is the intended service)
    curl -X DELETE https://api.elevenlabs.io/v1/voices/$VOICE_ID       -H "xi-api-key: $ELEVENLABS_API_KEY"

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

Against the Agent Skills spec

  • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Map keys must be unique at line 42, column 5: or call completed. Reports call transcripts and outcomes. always: false ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • warning description-short description under 40 chars: too little signal for triggering
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 5562 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 24/100

  • 0Steps. Prose only: no discrete steps
  • 0Result and completion. Does not say what the result is
  • 0When it triggers. No condition that starts the skill
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 4 mutating operations with no state check
  • 40Consistency. Frontmatter name (voice-agent) differs from the folder (voice-agent-v1)
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
  • 70Execution cost. Instruction body is 5562 tokens
  • 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)
  • +3Description length 1: 120–800 characters recommended
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +4Structure: 42 headings
  • +4Has examples (33 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 39.

External checks

ClawHub: suspicious
This voice-cloning and calling skill is mostly coherent, but it asks for broad account, credential, and telephony control without enough scoping or consent safeguards.
LLM: suspicious (high) · VirusTotal: · 29 May 2026