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by io.github.yichong1
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Text to sound effect (TangoFlux)

text_to_sound_effect

Generate a short sound-effect WAV from a text prompt via TangoFlux (async create + result poll). Pass prompt (<= 2000 chars) with optional duration (default 10s) and steps (default 25); the call waits up to wait_seconds (default 30, max 55) and returns job_id if still running. Poll by calling again with only job_id. Returns audio_url when done. Cost: 2 credits per call, charged by mcp-credit-gateway before forwarding. Compliance: Use only on material you own or are explicitly licensed/authorized to generate or remix. Do not generate or redistribute copyrighted music, voice likenesses, or trademarked audio without permission. Output URLs have a limited TTL and must not be abused for bulk scraping or redistribution. Calls are rate-limited/metered by mcp-credit-gateway and require a valid sk_live_ key. （仅处理自有或已获授权素材；禁止滥用生成/二创他人受版权保护的音乐或声音；输出有 TTL；调用限频。）

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "text_to_sound_effect"
  }
}

Input Schema

NameRequiredDescriptionDefault
stepsNoSampling steps (10–100, default 25).
job_idNoExisting TangoFlux job id from a previous call. Polling never creates a new upstream job.
promptNoText description of the sound effect to generate (<= 2000 chars). Required to start a new job; omit when polling with `job_id` only.
durationNoTarget duration in seconds (1–30, default 10).
wait_secondsNoHow long to wait for a result, 0–55 seconds (default 30). On timeout the call returns a job_id to poll.
idempotency_keyNoOptional caller correlation key, echoed in the result. Billing is handled by mcp-credit-gateway.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Goes well beyond the annotations: 2 credits per call charged by mcp-credit-gateway before forwarding, rate limiting/metering, a required sk_live_ key, and a limited TTL on output URLs. The async contract (create vs poll, max 55s wait, defaults for duration/steps) is disclosed in prose, which the readOnlyHint=false annotation alone would never communicate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The operational content is front-loaded and dense, but the compliance paragraph is then restated nearly verbatim in Chinese parentheses, which is pure duplication and adds length without new information. The result is longer than needed for the value delivered.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 6-parameter async generation tool with no output schema, the description covers everything an agent needs: inputs, polling protocol, returned fields (`audio_url`, `job_id`), cost, auth key requirement, and TTL. Nothing material about a correct invocation is left unstated.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds cross-parameter semantics the schema cannot: `prompt` starts a new job while `job_id`-only resumes an existing one without creating upstream work. Defaults for duration (10s), steps (25), and wait_seconds (30/55) are restated helpfully; `idempotency_key` is left to its schema text.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Generate a short sound-effect WAV from a text prompt via TangoFlux') and then explains the two-mode call shape (async create + result poll). 'Sound-effect WAV' implicitly separates it from the sibling text_to_speech, and the engine name is given, so an agent knows exactly what artifact comes back.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly tells the agent how to resume an unfinished job ('Poll by calling again with only `job_id`') and when the tool returns early (wait_seconds timeout yields job_id). It also scopes legitimate usage via the compliance paragraph. It does not, however, explicitly compare against siblings like text_to_speech or state when not to use this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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