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 agentmods add commands/michael-l-i/cadence-code/jump-ingit clone --depth 1 https://github.com/michael-L-i/cadence-codeWrote 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/michael-l-i/cadence-code/jump-in)<a href="https://agentmods.dev/commands/michael-l-i/cadence-code/jump-in"><img src="https://agentmods.dev/badge/commands/michael-l-i/cadence-code/jump-in.svg" alt="Measured on agentmods" 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 | $0.00006 | $0.00338 |
| Opus 5 | $0.00003 | $0.00169 |
| Sonnet 5 | $0.00001 | $0.00068 |
| Haiku 4.5 | $0.00001 | $0.00034 |
Grade A, and why
jump-in 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 4d 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
Interrupt the current Cadence Code audio and collect one fresh spoken
instruction with mcp__cadence-code__voice_interrupt. This command is intended
to be invoked after the user presses Escape to stop the current Claude Code
turn.
- Call
mcp__cadence-code__voice_interruptimmediately. Do not callvoice_start,voice_speak, or ordinaryvoice_listenfirst. - If it returns
ok: false, show the error. If Cadence Code is inactive, tell the user to run/cadence-code:start-talking; do not start it implicitly. - Treat every non-empty transcript as added guidance for the interrupted task,
including one returned with
end_reason: "timeout". Continue from current conversation and repository state without asking whether to resume. If the guidance redirects or replaces the work, follow it normally. - If no speech is detected, leave the interrupted task stopped, report that no guidance was captured, and do not listen again automatically.
- On
end_reason: "device_error", show the microphone problem and leave Cadence Code active so the user can retry or run/cadence-code:wrap-up. - If the transcript clearly asks to end Cadence Code entirely, call
mcp__cadence-code__voice_stopand do not resume the task.
After accepting the guidance, continue the normal Cadence Code workflow: work silently, then provide the concise spoken result and detailed written result before listening for the next turn.
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.
- 4d ago First seen · 28 lines · 6 tokens per session scan A 10b87fbc3425
jump-in is a command published in the GitHub repository michael-L-i/cadence-code (2 stars, last pushed 4d ago), licensed MIT. It adds 6 tokens to every session and 338 once invoked, about $0.0000 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
summary-say
Summarize and speak the last response.
tts-init
Install MLX dependencies and download model (4GB).
tts-mute
Temporarily mute TTS notifications.
tts-start
Start TTS server to keep model warm.
tts-status
Check TTS server status and configuration.
tts-stop
Stop the TTS server to reclaim GPU memory.