Borrowing it
Nothing to install: this file belongs to taylorbrook/MAX-MSP_CC_Framework. 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/taylorbrook/MAX-MSP_CC_Framework/main/.claude/skills/max-dsp-agent/SKILL.mdgit clone --depth 1 https://github.com/taylorbrook/MAX-MSP_CC_FrameworkWrote 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/taylorbrook/max-msp_cc_framework/max-dsp-agent)<a href="https://agentmods.dev/skills/taylorbrook/max-msp_cc_framework/max-dsp-agent"><img src="https://agentmods.dev/badge/skills/taylorbrook/max-msp_cc_framework/max-dsp-agent/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/taylorbrook/max-msp_cc_framework/max-dsp-agent"><img src="https://agentmods.dev/badge/skills/taylorbrook/max-msp_cc_framework/max-dsp-agent.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 | $0.00021 | $0.07749 |
| Opus 5.5 | $0.00008 | $0.03100 |
| Sonnet 5.5 | $0.00004 | $0.01550 |
| Haiku 4.5 | $0.00002 | $0.00775 |
Grade A, and why
max-dsp-agent scanned grade A with 1 finding 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 6d 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
result = subprocess.run( How it starts
The opening of the file, as written. The whole thing — 436 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DSP/Gen~ Specialist Agent
The DSP agent generates audio signal processing components: GenExpr code for gen~ objects, MSP signal chains, and audio effect architectures. It handles everything that operates at audio rate.
Domain Context Loading
Before any generation:
- Read
CLAUDE.mdat project root -- follow MSP and Gen~ domain-specific rules - Read
.claude/skills/references/genexpr-rules.mdbefore writing or editing any GenExpr (codebox,.gendsp,mc.gen~) -- the full gen~ rule set with derivations and evidence - Use
ObjectDatabasefromsrc.maxpat.db_lookupfor all object lookups -- it loads all domains, resolves aliases, and checks PD blocklist automatically. No need to read individual domain JSON files. - Check
.claude/max-objects/pd-blocklist.jsonif you need to browse PD equivalents in bulk - Read project
config.jsonviaload_project_config()fromsrc.maxpat.projectfor allowed packages. Passallowed_packagestoPatcher(allowed_packages=allowed)so package objects outside the project's selection are blocked at creation time. Ifload_project_config()returns None (no config.json), useallowed = [](core-only), never None -- None allows every package.
Domain focus: MSP (signal processing) and Gen~ (DSP operators). Other domains are handled by their respective agents.
Capabilities
GenExpr Code Generation
build_genexpr(params, code_body, num_inputs=1, num_outputs=1)-- build validated GenExpr code stringparse_genexpr_io(code)-- detect input/output count from GenExpr codegenerate_gendsp(code, num_inputs=None, num_outputs=None)-- generate standalone .gendsp JSON dictwrite_gendsp(code, path, num_inputs=None, num_outputs=None)-- write a .gendsp file: a new path is generated; an existing file is edited in place (codeboxcodereplaced,in N/out Nboxes synced to the code's I/O, everything else kept; removed cords come back inresult.orphaned) (imported fromsrc.maxpat.hooks, not fromsrc.maxpat.patcher)- GenExpr syntax:
in1/out1for I/O (no space -- space form is for gen~ patcher objects only),Paramfor parameters,Historyfor feedback,Buffer/Datafor samples - Declaration ordering rule: ALL declarations (
Param,Delay,History,Buffer,Data) MUST appear at the top of the codebox, before any expressions or assignments. GenExpr enforces this strictly -- mixing declarations with expressions causes "declarations must come before any expressions" errors. Group declarations by type: Params first, then Delays, then History, then Buffer/Data.
What ships with it
1 file 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.
- 6d ago Changed · +34 lines ba504f63fd59
- 7d ago Changed · +12 lines a937dee768e3
- 13d ago Changed 45daf4f178ff
- 14d ago Changed · -4 lines 2fa6bee5c2c5
- 15d ago Changed · +3 lines af429a49a1e8
- 16d ago Changed 55c26d01456c
- 2mo ago First seen · 391 lines · 21 tokens per session scan A df20abcf5efe
max-dsp-agent is a skill published in the GitHub repository taylorbrook/MAX-MSP_CC_Framework (46 stars, last pushed 4d ago), licensed MIT. It adds 21 tokens to every session and 7,749 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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