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 tdmcp-ai-party-mixer-designgit 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/tdmcp-ai-party-mixer-design)<a href="https://agentmods.dev/skills/pantani/tdmcp/tdmcp-ai-party-mixer-design"><img src="https://agentmods.dev/badge/skills/pantani/tdmcp/tdmcp-ai-party-mixer-design/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/tdmcp-ai-party-mixer-design"><img src="https://agentmods.dev/badge/skills/pantani/tdmcp/tdmcp-ai-party-mixer-design.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 | $0.00103 | $0.01090 |
| Opus 5 | $0.00051 | $0.00545 |
| Sonnet 5 | $0.00021 | $0.00218 |
| Haiku 4.5 | $0.00010 | $0.00109 |
Grade A, and why
tdmcp-ai-party-mixer-design 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- tdmcp-ai-party-mixer-design — 100% identical, 0 lines differ
- tdmcp-ai-party-mixer-design — 100% identical, 0 lines differ
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.
tdmcp-ai-party-mixer-design
Coordinate the mixer-aware AI-Controlled Party design team. This harness produces an implementation-ready spec for the operator-approved Soundcraft Ui24R scene-arming MVP. It does not build runtime code directly.
Execution mode: sub-agent fan-out -> lead synthesis
This repo's existing harnesses run as sub-agents in this environment. Use
parallel sub-agents for the specialist lanes, then synthesize in one lead pass.
All agent calls use model: "opus".
Agent roster
| Agent | Skill | Output |
|---|---|---|
mixer-scene-contract-architect |
mixer-scene-contract |
_workspace/ai-party-mixer/01_contract.md |
soundcraft-ui24r-adapter-architect |
soundcraft-ui24r-adapter |
_workspace/ai-party-mixer/02_adapter.md |
mixer-policy-safety-qa |
mixer-policy-safety |
_workspace/ai-party-mixer/03_policy_qa.md |
ai-party-mixer-runbook-writer |
ai-party-mixer-runbook |
_workspace/ai-party-mixer/04_runbook_docs.md |
ai-party-mixer-lead |
this orchestrator context | _workspace/ai-party-mixer/05_synthesis_design.md and optional durable spec |
Phase 0 - context check
- Check whether
_workspace/ai-party-mixer/exists. - Decide run mode:
- no directory -> fresh run;
- directory exists + user asks to revise one part -> partial re-run of only affected specialists, then lead synthesis;
- directory exists + materially new objective -> move it to
_workspace/ai-party-mixer_<YYYYMMDD_HHMMSS>/, then fresh run.
- Read the current AI-Controlled Party docs/spec and
show-directorschema before spawning specialists.
Phase 1 - prepare
Create _workspace/ai-party-mixer/00_input.md with:
- user objective;
- selected MVP mode: operator-approved scene arming;
- known mixer: Soundcraft Ui24R;
- explicit non-goals: gain, PA mute, routing, channel edits, autonomous hardware execution;
- questions or assumptions that still need bench validation.
Phase 2 - specialist fan-out
Spawn the four specialist agents in one message when possible. Each prompt must:
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 · 103 tokens per session scan A 45e73aee3d5e
tdmcp-ai-party-mixer-design is a skill published in the GitHub repository Pantani/tdmcp (41 stars, last pushed 27d ago), licensed MIT. It adds 103 tokens to every session and 1,090 once invoked, about $0.0005 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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