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Audit captions

audit_captions

PROJECT-SCOPED: this call acts only on the explicit project_id and returns the project identity with its result. Mechanically compile and audit the CURRENT caption track using the exact ASS artifact ffmpeg burns. Reports first-caption lateness, missing spoken-word coverage, true distinct-state overlaps, max_words_seen, max_lines_seen, declared-density and single-line wrap violations, exact event pages and up to 16 high-information output times for rendered pixel QA. Call after adding or restyling captions and after render_preview; this is stronger timing evidence than a visual critic.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
offsetNo
project_idYesRequired immutable scope for this call. Copy the id from list_projects/open_project/project_state; the active-project pointer is never used to guess.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

With annotations all false, the description carries the burden, and it delivers useful behavioral details: it is project-scoped, uses the exact ASS artifact that ffmpeg burns, returns project identity with the result, and lists exact metrics and output times. It does not explicitly state whether state is modified, but the audit semantics and output framing make the behavior reasonably clear.

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

Conciseness4/5

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

The description is dense but mostly high-value, front-loading the critical project-scoped constraint. The long mid-sentence list of metrics is packed with useful information, though it would be easier to parse if broken into shorter sentences.

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, the description does well by enumerating the reported metrics, event pages, and output times. The only notable gap is the lack of any guidance on limit and offset, which leaves the pagination behavior ambiguous.

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

Parameters2/5

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

Schema coverage is only 33%, with limit and offset completely undocumented in the schema. The description clarifies project_id's required immutable scope and how to source it, but it does not explain limit or offset at all, so it fails to compensate for the low schema coverage.

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 uses a specific verb and resource: it audits the current caption track, and is explicitly marked PROJECT-SCOPED. It also distinguishes itself by naming what it reports and by comparing itself to a visual critic, making it easy to differentiate from siblings like audit_audio_mix.

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?

It explicitly tells the agent when to call this tool: after adding or restyling captions and after render_preview. It also provides a exclusionary reason by stating it is stronger timing evidence than a visual critic, which helps select the correct tool among alternatives.

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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