Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add automateyournetwork/netclaw --skill slack-voice-interfacegit clone --depth 1 https://github.com/automateyournetwork/netclawWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/automateyournetwork/netclaw/slack-voice-interface)<a href="https://agentmods.dev/skills/automateyournetwork/netclaw/slack-voice-interface"><img src="https://agentmods.dev/badge/skills/automateyournetwork/netclaw/slack-voice-interface/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/automateyournetwork/netclaw/slack-voice-interface"><img src="https://agentmods.dev/badge/skills/automateyournetwork/netclaw/slack-voice-interface.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00065 | $0.00888 |
| Opus 5 | $0.00032 | $0.00444 |
| Sonnet 5 | $0.00013 | $0.00178 |
| Haiku 4.5 | $0.00006 | $0.00089 |
Grade A, and why
slack-voice-interface scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Slack Voice Interface
How It Works
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
Voice Response Workflow
Step 1: Process the question
Treat the transcribed voice message identically to a typed text message. Use the full NetClaw skill set — pyATS, NetBox, ServiceNow, etc.
Step 2: Generate voice response
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:
python3 $MCP_CALL "python3 -u $TTS_MCP_SCRIPT" list_voices '{"language":"en"}'
Step 3: Deliver both text and voice
Post the text response in the Slack thread AND upload the MP3 file:
:loud_speaker: Voice Response [MP3 audio file attached]
R1 has 3 OSPF neighbors, all in FULL state on Area 0:
- 2.2.2.2 (R2) via Gi1 — FULL/DR
- 3.3.3.3 (R3) via Gi2 — FULL/BDR
Always deliver text AND voice. Text is primary (searchable, accessible). Voice is supplementary.
Voice Selection
| Voice | Description |
|---|---|
| en-US-GuyNeural | Professional male — default |
| en-US-JennyNeural | Professional female |
| en-US-AriaNeural | Conversational female |
| en-GB-RyanNeural | British male |
Users can request a voice change:
- "Switch to a female voice" → use en-US-JennyNeural
- "Use a British accent" → use en-GB-RyanNeural
Call list_voices to see all 300+ available voices.
Performance
| Phase | Latency |
|---|---|
| edge-tts synthesis | 1-2 seconds |
| Slack MP3 upload | < 1 second |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 112 lines · 65 tokens per session scan A 701b49e6ff04
slack-voice-interface is a skill published in the GitHub repository automateyournetwork/netclaw (657 stars, last pushed 6d ago), licensed Apache-2.0. It adds 65 tokens to every session and 888 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…