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ass_style_usage

Count how styles, actors, or effects are used in an Aegisub/ASS document, see dialogue and comment totals, and list unused or unknown styles to clean up subtitle scripts.

Instructions

Count how styles and actors are used, and name the unused styles.

Args: doc_id: document id or None for the current document. by: which grouping goes in counts: "style", "actor" or "effect".

Returns: {"doc_id", "by", "counts", "by_style", "by_actor", "unused_styles", "unknown_styles", "lines"}. Each count bucket is {"name", "total", "dialogue", "comment"}; unknown_styles maps a style referenced by lines but absent from the style section to its line count.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
byNostyle
doc_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full burden. It discloses deterministic counting behavior and the exact return shape, but says nothing about read-only status, side effects, permissions, or rate limits; for a query tool this is a notable but not fatal gap.

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?

Front-loads purpose, then uses Args and Returns sections. The Returns block is detailed and partly overlaps the output schema, but its semantic notes, such as count bucket fields and the unknown_styles mapping, earn their place; overall tight and well-structured.

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?

An output schema exists, so return structure is already covered, and the Args section fully compensates for 0% schema coverage on both parameters. Missing explicit usage routing and safety context, but sufficient for correct invocation.

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 description coverage is 0%, but the Args section fully compensates: doc_id is 'document id or None for the current document' and by accepts 'style', 'actor', or 'effect'. This adds syntax, default meaning, and value semantics beyond the bare schema types.

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+resource: count how styles and actors are used, and name unused styles. Distinguishes from style-related siblings like ass_list_styles or ass_get_style by focusing on usage counts and unused styles rather than listing or retrieving individual styles.

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

Usage Guidelines3/5

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

No explicit when-to-use or alternatives are given, but the purpose and Args clearly imply the tool is for auditing style/actor/effect usage. The absence of sibling routing, such as to ass_stats, leaves the guidance implied rather than stated.

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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