SKILLEMALL.ai

BB liber-speechapi

Use Liber SpeechAPI for three speech workflows: (1) Telegram/openclaw voice-message handling with ASR, concise reply summarization, and Telegram-compatible OGG/Opus TTS, (2) direct text-to-speech generation when the user explicitly asks to synthesize text into audio, and (3) direct speech-to-text transcription when the user explicitly asks to convert audio into text or structured JSON. Support environment-based configuration, optional voice cloning from a reference audio file, and fallback between shared python-env skill and the local Python environment.

Not recommendedcritical or high security findings
ClawHub Agent Skills author: chang v1.1.0 MIT-0 12 files body ≈ 1 084 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 70/100 · Nearly there — weak spots: inputs and preconditions, running it twice

ProcedureTelegramGitHubSoftware developmentInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
78/100
safety, quality, tests
Safety 60%
76
Quality 40%
80
Run on models
none yet
Process rating
B
70/100
Nearly there
Inputs and preconditions w 11
0
Running it twice w 4
30
Tools and files w 18
60
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Secrets in code
If you install

The files contain someone else's key or token. If it is live, your agent will call third-party services under a stranger's identity; if it was revoked, the skill's scripts simply fail. Such a key often arrives with the author's whole workspace, personal data included.

For the author

The key is visible to everyone who downloaded the skill and has likely been copied by catalog-scanning bots already. Revoke it now, check bills and access logs, then reissue.

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. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
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 · 3

  • high Secrets in code meta-credential-files .env
    Credential / dotenv files bundled with the skill (1)
    .env
Medium and low: 2
  • medium Exfiltration net-redirectable-api-key scripts/liber_speech_client.py:123
    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 Exfiltration read-dotenv references/config.md:171
    Reads a .env file
    copy .env.example .env

Files scanned: 11. 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: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Use Liber SpeechAPI for three speech workflows: (1) Telegram/openc… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value

Process rating: all ten parameters 70/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 3 mutating operations with no state check
  • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 54 steps
  • 100Failures and branches. 5 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1084 tokens
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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)
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +3Description length 560: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 54 items
  • +3Output format is stated explicitly
  • +4Reference files are cited in the instructions (4 of 4)
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.

External checks

ClawHub: suspicious
This speech skill does what it claims, but it handles voice data and API credentials in ways users should review before installing.
LLM: suspicious (high) · VirusTotal: · 29 May 2026