Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add Pr1m4lc0d3/wheel-to-talk/plugin install wheel-to-talkWrote 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/commands/pr1m4lc0d3/wheel-to-talk/wheel-to-talk-setup)<a href="https://agentmods.dev/commands/pr1m4lc0d3/wheel-to-talk/wheel-to-talk-setup"><img src="https://agentmods.dev/badge/commands/pr1m4lc0d3/wheel-to-talk/wheel-to-talk-setup/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/commands/pr1m4lc0d3/wheel-to-talk/wheel-to-talk-setup"><img src="https://agentmods.dev/badge/commands/pr1m4lc0d3/wheel-to-talk/wheel-to-talk-setup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00011 | $0.00154 |
| Opus 5 | $0.00005 | $0.00077 |
| Sonnet 5 | $0.00002 | $0.00031 |
| Haiku 4.5 | $0.00001 | $0.00015 |
Grade A, and why
wheel-to-talk-setup scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Run the Wheel to Talk setup script and report its output to the user verbatim:
node "${CLAUDE_PLUGIN_ROOT}/scripts/setup.mjs"
The script is deterministic and does all the work — do not attempt to edit the
user's settings.json yourself, and do not install AutoHotkey for them.
If it reports AutoHotkey is missing, show them the winget command and stop.
Do not run it on their behalf without asking.
If it succeeds, tell them to hold the middle mouse button in the terminal,
speak, and release — and that releasing sends the prompt immediately, because
autoSubmit is on.
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.
- 10d ago First seen · 20 lines · 11 tokens per session scan A 30603bdac620
wheel-to-talk-setup is a command published in the GitHub repository Pr1m4lc0d3/wheel-to-talk (1 stars, last pushed 13d ago), licensed MIT. It adds 11 tokens to every session and 154 once invoked, about $0.0001 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 2026-08-31.
Other commands, from other repositories
start-talking
Start talking with Cadence Code.
jump-in
Jump In and add spoken guidance.
voice-settings
Choose Cadence Code speech models.
wrap-up
End the active Cadence Code conversation.
stts
User speaks the prompt, which is sent to the Model, the received response is spoken/read aloud in a loop.
prototype
You are building a proof-of-concept for the current Grainulator sprint. Read CLAUDE.md for sprint context and claims.json for existing research claims.