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 Pantani/tdmcp --skill soundcraft-ui24r-adaptergit clone --depth 1 https://github.com/Pantani/tdmcpWrote 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/pantani/tdmcp/soundcraft-ui24r-adapter)<a href="https://agentmods.dev/skills/pantani/tdmcp/soundcraft-ui24r-adapter"><img src="https://agentmods.dev/badge/skills/pantani/tdmcp/soundcraft-ui24r-adapter/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/pantani/tdmcp/soundcraft-ui24r-adapter"><img src="https://agentmods.dev/badge/skills/pantani/tdmcp/soundcraft-ui24r-adapter.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 | $0.00081 | $0.00351 |
| Opus 5 | $0.00041 | $0.00176 |
| Sonnet 5 | $0.00016 | $0.00070 |
| Haiku 4.5 | $0.00008 | $0.00035 |
Grade A, and why
soundcraft-ui24r-adapter 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 8d 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- soundcraft-ui24r-adapter — 100% identical, 0 lines differ
- soundcraft-ui24r-adapter — 100% identical, 0 lines differ
What it actually says
soundcraft-ui24r-adapter
Design the adapter boundary between an approved mixer scene plan and Soundcraft Ui24R control.
Context to read
- AI-Controlled Party docs/spec
- current
show-directorruntime and CLI files - any user-provided venue, mixer, or network notes
Use live web research only when making precise current claims about third-party APIs. If not verified, mark the detail as a bench-test requirement.
Backend order
- Dry-run/simulated: always first; no hardware dependency.
- Bitfocus Companion: preferred first live bridge for stage reliability and operator familiarity.
- Direct Node bridge: later path using a Soundcraft connection library, only after the contract and policy are stable.
Adapter scope
MVP allows only show/snapshot/cue loading after operator approval. Exclude gain, PA mute, routing, phantom power, and channel edits.
Output
Write _workspace/ai-party-mixer/02_adapter.md with interface shape, backend
options, required config, health checks, failure modes, and validation gates.
Quality bar
The design must make it impossible to confuse "approval returned a plan" with "hardware definitely changed state".
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.
- 8d ago First seen · 42 lines · 81 tokens per session scan A db78dad14ac0
soundcraft-ui24r-adapter is a skill published in the GitHub repository Pantani/tdmcp (39 stars, last pushed 27d ago), licensed MIT. It adds 81 tokens to every session and 351 once invoked, about $0.0004 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.
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