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Get Started Free →automateyournetwork/slack-voice-interface
Respond to Slack voice clips with both text and an MP3 voice reply using edge-tts. Voice IN is already handled by OpenClaw transcription.
Passed 16 of 20 test cases with the skill, and 5 of 20 without it.
and 12 more in the full report
13 fixed5 passed either way4 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 12 test cases the skill fixed. Same model, same prompt, with and without the skill.
Provide the exact CLI command structure to execute text_to_speech using the $MCP_CALL and $TTS_MCP_SCRIPT environment variables.
| Checked | Without skill | With skill |
|---|---|---|
| Formats command as python3 $MCP_CALL "python3 -u $TTS_MCP_SCRIPT" text_to_speech '{"text":"...","voice":"..."}'. | Missed | Passed |
The instructions your model reads when the skill loads.
User sends voice clip in Slack
|
v
OpenClaw transcribes automatically (built-in)
|
v
NetClaw processes with full skill set
(pyATS, NetBox, ServiceNow, all 40 MCP servers)
|
v
python3 $MCP_CALL "python3 -u $TTS_MCP_SCRIPT" text_to_speech → MP3 file
|
v
Upload MP3 to Slack thread + post text response
Treat the transcribed voice message identically to a typed text message. Use the full NetClaw skill set — pyATS, NetBox, ServiceNow, etc.
After composing your text response, call text_to_speech:
python3 $MCP_CALL "python3 -u $TTS_MCP_SCRIPT" text_to_speech '{"text":"R1 has 3 OSPF neighbors, all in FULL state on Area 0...","voice":"en-US-GuyNeural"}'
This returns JSON with an output_path to the generated MP3 file.
To list available voices:
test cases passed, vs 5 / 20 without
Published skills whose descriptions closely match this one, with their headline benchmark lift.
More skills from the same source and nearby in the registry, with their headline benchmark lift.