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forced_alignment

Align a known transcript to existing audio to obtain exact per-word timings, enabling precise captions, lip-sync, and cut timing.

Instructions

Align a KNOWN script to existing audio → exact per-word timings (ElevenLabs).

Use when you already have the exact transcript (a recorded VO + its script) and want precise timings for captions/lip-sync/cut timing. (Unlike transcribe, which discovers the words — this snaps your given text to the audio.)

Args: audio: Local audio file path. text: The exact transcript/script spoken in the audio. captions: "srt" or "vtt" to also write a subtitle file from the aligned words.

Returns: {"words": , "characters": , "loss", "captions_path"?} or {"error"}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
audioYes
captionsNo
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses the core behavior (snapping text to audio), the output format (word/character counts, loss, captions path), and optional caption writing. However, it does not explain what 'loss' means or how mismatches between script and audio are handled, leaving some behavioral ambiguity.

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 well-structured with intro, usage guidance, args, and returns. Every sentence contributes value; no fluff. It is longer than typical but earns its length with dense, useful information.

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 tool with no output schema and no annotations, the description is quite complete: it explains purpose, args, return values, and usage context. However, the 'loss' return field is left undefined, and error conditions or failure modes are not mentioned, leaving minor gaps.

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

Parameters5/5

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

Schema has 0% description coverage, but the Args section fully compensates: audio ('Local audio file path'), text ('exact transcript/script'), captions ('srt' or 'vtt' to also write a subtitle file'). This adds meaning well beyond the bare titles in the schema.

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 opens with a specific verb and resource: 'Align a KNOWN script to existing audio → exact per-word timings'. It clearly distinguishes the tool from siblings by contrasting with `transcribe`, which discovers words, while this snaps given text to audio.

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

Usage Guidelines5/5

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

Explicitly states when to use: 'Use when you already have the exact transcript...' and names the alternative (`transcribe`) with a clear distinction. This gives the agent actionable selection criteria.

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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