Borrowing it
Nothing to install: this file belongs to zarfld/presonus-studiolive-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/zarfld/presonus-studiolive-mcp/master/.github/Skills/presonus-fat-channel-selection/SKILL.mdgit clone --depth 1 https://github.com/zarfld/presonus-studiolive-mcpWrote 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/zarfld/presonus-studiolive-mcp/presonus-fat-channel-selection)<a href="https://agentmods.dev/skills/zarfld/presonus-studiolive-mcp/presonus-fat-channel-selection"><img src="https://agentmods.dev/badge/skills/zarfld/presonus-studiolive-mcp/presonus-fat-channel-selection/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/zarfld/presonus-studiolive-mcp/presonus-fat-channel-selection"><img src="https://agentmods.dev/badge/skills/zarfld/presonus-studiolive-mcp/presonus-fat-channel-selection.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 | $0.00132 | $0.02863 |
| Opus 5 | $0.00066 | $0.01432 |
| Sonnet 5 | $0.00026 | $0.00573 |
| Haiku 4.5 | $0.00013 | $0.00286 |
Grade A, and why
presonus-fat-channel-selection 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 12d 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 — 212 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PreSonus Fat Channel Selection Skill
Purpose
Help an agent choose, inspect, or explain StudioLive III / 32SC Fat Channel compressor and EQ models without hallucinating capabilities.
This skill covers:
- Selecting compressor and EQ model families for a channel, bus, monitor mix, or mix target.
- Reading current model state through the StudioLive MCP resources when available.
- Mapping model names to live indices and
__classidGUIDs for scene-file work. - Explaining what the human operator should change in UC Surface when MCP writes are not available.
Default behavior
Use a recommendation-first workflow. Do not present every available model as an equal menu. Pick a primary recommendation, give one fallback when useful, and explain the tradeoff in source-specific terms.
When the user asks for current mixer state, inspect resources first. When the user asks for offline advice, make an explicit assumption list and proceed without MCP reads.
Required inputs
Extract these from the user request or mixer state:
- Source: kick, snare, bass DI, bass amp, guitar, vocal, drum bus, mix bus, aux/wedge/IEM, etc.
- Goal: transparent control, punch, warmth, glue, vintage color, feedback resistance, monitor comfort, or sidechain/ducking.
- Channel context: line input, aux, sub, FX return, main, linked stereo pair, bus, or scene file.
- Availability constraint: factory-only vs. Fat Channel Collection add-ons allowed. If unknown, prefer factory-safe options or mark add-on picks as “if installed.”
Ask for clarification only when a missing input changes the recommendation materially. Otherwise use sensible defaults and state them briefly.
High-level workflow
- Classify the request:
- Recommend: choose model(s) and explain why.
- Inspect: read current mixer state via MCP resources.
- Scene/GUID: map names to live indices and
__classidvalues. - Debug/validate: check whether state, schemas, or channel type support the requested operation.
- Check the hard constraints in Gotchas before answering.
- Use the quick selector below for first-pass model choice.
- Load reference files only as needed:
- Read
references/fat-channel-model-catalog.mdfor detailed model descriptions and selector tables. - Read
references/mcp-interface-and-schemas.mdfor MCP tools, resources, raw key paths, schemas, and write-status details. - Read
references/guid-mapping.mdfor exact GUID/class ID values.
- Read
- Return an actionable answer with either manual UC Surface steps or a read-only MCP inspection summary.
- Run the validation checklist before finalizing.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 212 lines · 132 tokens per session scan A 78dd0b562990
presonus-fat-channel-selection is a skill published in the GitHub repository zarfld/presonus-studiolive-mcp (1 stars, last pushed yesterday), licensed MIT. It adds 132 tokens to every session and 2,863 once invoked, about $0.0007 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.
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