SKILLEMALL.ai

BC webchat-voice-full-stack

One-step full-stack installer for OpenClaw WebChat voice input with local speech-to-text. Deploys faster-whisper STT backend plus HTTPS/WSS WebChat proxy with mic button in one command. Push-to-Talk (hold to speak) and Toggle mode with keyboard shortcuts (Ctrl+Space PTT, Ctrl+Shift+M continuous recording). Real-time VU meter, localized UI (English, German, Chinese), interactive language selection during install. No recurring API costs, runs fully local after initial model download (~1.5 GB). Combines faster-whisper-local-service and webchat-voice-proxy. Keywords: voice input, microphone, WebChat, speech to text, STT, local transcription, whisper, full stack, one-click, voice button, push-to-talk, PTT, keyboard shortcut, i18n.

modbender/skill-library-mcp Agent Skills author: modbender MIT 4 files · 2 scripts body ≈ 690 tokens Open the sourcegithub.com analyzed 3 d ago

One-step full-stack installer for OpenClaw WebChat voice input with local speech-to-text.

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches

IntegrationInfrastructureSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
71
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
0
Progress reporting w 2
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.
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: 4. 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")

Process rating: all ten parameters 51/100

  • 0Result and completion. Does not say what the result is
  • 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. 8 mutating operations with no state check
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 19 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 690 tokens

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
  • -41 reference files, but SKILL.md never points to them: the model will not open them
  • +1No license
  • +2Single-language instructions
  • +3Description length 735: enough signal without eating the budget
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 19 items
  • +4Has examples (5 code blocks)
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.