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gaudiolab-jp

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gaudio_sync_lyrics

Synchronize lyrics with audio timestamps by uploading files to generate CSV outputs containing line-level timing data, text alignment, and confidence scores.

Instructions

All-in-one lyrics sync: upload audio + text files → create gts_lyrics_line_v1 job → poll → return CSV (timestamp, lyric_text, confidence_score) + JSON report URLs. Text file requirements: .txt format, UTF-8, minimum 2 lines, max 60 characters per line. Audio limit: 1GB / 10 minutes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
audioFilePathNoPath to local audio file. Either audioFilePath or audioUploadId required.
audioUploadIdNoExisting audio uploadId to reuse.
textFilePathNoPath to local .txt lyrics file. Either textFilePath or textUploadId required.
textUploadIdNoExisting text uploadId to reuse.
languageYesLanguage of the lyrics: en (English), ko (Korean), ja (Japanese), zh-cn (Chinese Simplified)
pollIntervalNoPolling interval in seconds (default: 10)
Behavior4/5

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

With no annotations provided, the description carries full behavioral disclosure burden. It successfully reveals: asynchronous polling nature, specific job type created (gts_lyrics_line_v1), return structure (CSV + JSON URLs), file constraints (UTF-8, 60 char limit), and size limits (1GB/10min). Could improve by mentioning failure modes or blocking behavior.

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?

Extremely efficient: first sentence establishes entire workflow with arrow notation; second sentence packs all file and audio constraints. No redundancy. Every clause delivers novel information beyond schema.

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?

Excellent coverage for a 6-parameter async job tool lacking output schema. Compensates by detailing return format (CSV columns), input validation rules, and pipeline stages. Only minor gaps: missing duration estimates, retry behavior, or error handling specifics.

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% with adequate individual parameter descriptions, establishing baseline 3. Description adds significant value by specifying file content requirements (.txt, UTF-8, min 2 lines, max 60 chars) and audio constraints (1GB/10min) not present in parameter descriptions, plus return value semantics.

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?

Description uses specific verb chain ('upload → create → poll → return') and identifies exact resource (lyrics sync) and output format (CSV with timestamp/lyric_text/confidence_score). 'All-in-one' clearly positions this as an end-to-end workflow distinct from sibling tools like gaudio_upload_file and gaudio_create_job.

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 'All-in-one' framing implies this is a convenience wrapper for the complete pipeline, distinguishing it from siblings that handle individual steps (upload_file, create_job, get_job). However, it lacks explicit 'when not to use' guidance (e.g., if files are already uploaded or custom polling is needed).

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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