CCAPI

Extend a song

extend_music

Continue an existing song from a given timestamp, producing a longer version. Requires the clip_id of a previously generated song, which appears in the 'raw' payload of a completed generate_music task. Asynchronous — poll with get_task.

Input Schema

TableJSON Schema

Name	Required	Description
`tags`	No	Style tags for the extension.
`title`	No	New title for the extended song.
`prompt`	No	Lyrics for the extended section.
`clip_id`	Yes	ID of the song to extend, taken from the 'raw' clip list of a completed generate_music task.
`provider`	No	Music backend: 'suno' (default) or 'producer'.
`continue_at`	Yes	Timestamp in seconds within the original song to continue from.
`wait_seconds`	No	Poll server-side for up to this many seconds (max 240).

Output Schema

TableJSON Schema

Name	Required	Description
`raw`	No	Full result payload when completed — clip IDs, lyrics text and per-clip metadata. Clip IDs from here are what extend_music takes.
`note`	Yes	What to do next.
`status`	Yes	One of: queued, in_progress, completed, failed.
`task_id`	Yes	Pass this to get_task together with platform to check progress.
`platform`	Yes	'suno' or 'producer'. Pass to get_task.
`audio_urls`	No	Finished audio URLs, when the task completed within wait_seconds.

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already cover mutability and non-idempotency, so the description's added value lies in disclosing the asynchronous nature and the required prerequisite workflow. It explicitly states the clip_id source and that polling with get_task is needed, which goes beyond the structured annotation data.

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

Conciseness5/5

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

The description is three tight sentences with no filler. It front-loads the core purpose, then gives the required dependency, and closes with the asynchronous polling instruction. Every sentence earns its place.

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

Completeness4/5

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

For a mutation tool with an output schema and full parameter descriptions, the description covers the essential workflow: source of the clip_id, continuation behavior, and polling mechanism. It does not describe edge cases or failure modes, but the provided annotations and schema make this reasonably complete.

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 baseline is 3. The description adds meaningful semantics by tying clip_id to the raw payload of a completed generate_music task and by framing continue_at as a timestamp within the original song. This gives the agent practical understanding beyond the schema's bare definitions.

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?

The description clearly states a specific action ('Continue an existing song from a given timestamp'), the resource (a previously generated song), and the outcome ('producing a longer version'). It naturally distinguishes itself from generate_music by emphasizing that it operates on an existing clip rather than creating from scratch.

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?

The description gives concrete usage context: it requires a clip_id from a completed generate_music task and tells the agent to poll with get_task. It does not explicitly name alternatives or exclusion conditions, but the dependency and follow-up workflow are clear enough to guide tool selection.

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

All CCAPI tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.4/5.0

Disambiguation5/5

Each tool maps to a distinct media type or lifecycle step: text, image, music, video, task status, balance, and model discovery. The adjacent tools like edit_image vs generate_image and generate_lyrics vs generate_music are explicitly cross-referenced in their descriptions, so an agent can reliably pick the right one.

Naming Consistency4/5

All but one tool follows a clear imperative verb_noun pattern: edit_image, generate_music, get_task, list_models, etc. chat_completion is the lone structural outlier, using a noun phrase instead of a verb-led action name, which is a minor but noticeable inconsistency.

Tool Count5/5

11 tools is well-scoped for a multimodal API: one generation tool per media type, plus task polling, model listing, and balance checking. There is no redundancy or bloat, and each tool earns its place in the set.

Completeness4/5

The surface covers the full asynchronous workflow—submit generation, poll status, retrieve results—plus model discovery and quota awareness, so there are no dead ends. It lacks conveniences like cancelling a queued task or listing historical tasks, but those are minor gaps rather than blockers for the stated purpose.

Resources

Need Help?