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ass_get_line

Retrieves full detail for a single 0-based ASS subtitle line, including fields, override tags, drawing, karaoke, style, and timing data.

Instructions

Full detail for a single line (0-based index).

Returns the ass_list_lines line dict extended with:

  • fields — every field of the line exactly as stored.

  • tags_summary — override-tag counts/structure.

  • drawing{"active", "state", "segments", "drawing_segments", "prefix", "path", "suffix"}.

  • karaoke{"has_karaoke", "kinds", "total_ms", "syllables"} with per-syllable start/end times resolved against the line timing.

  • style/resolved_style — the style name, and the same name only when that style actually exists in the document (else None).

  • timing{"start_ms", "end_ms", "duration_ms", "start", "end", "cps", "characters", "lines"}.

Line indices are 0-based.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
indexYes
doc_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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 does disclose genuine behavioral detail — that resolved_style is None when the style is absent from the document and that karaoke syllable times are resolved against line timing — but says nothing about error behavior for an out-of-range index or the doc_id fallback.

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

Conciseness3/5

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

The purpose is front-loaded and the bulleted structure is scannable, but the bulk of the text enumerates return keys that an output schema already describes, so several lines do not earn their place against the structured data.

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

Completeness3/5

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

With an output schema present, the exhaustive return-value listing is largely redundant, while the genuinely missing pieces — doc_id meaning and out-of-range index behavior — go unexplained. It is adequate but leaves clear gaps for a 2-parameter tool.

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

Parameters3/5

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

Schema description coverage is 0%, so the description must compensate. It usefully clarifies that index is 0-based and refers to a line, but doc_id is never explained at all, leaving half the parameters undocumented in both schema and prose.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The opening line names a specific verb and resource (full detail for a single line) and distinguishes it from the bulk sibling by framing the result as the ass_list_lines dict extended with extra keys. It does not explicitly route the agent between the two, but the 'extends ass_list_lines' framing makes the distinction inferable.

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?

Usage is implied by 'Full detail' versus the list variant, but there is no explicit when-to-use/when-not statement and ass_list_lines is never named as the alternative for bulk reads. An agent must infer the routing from the phrasing alone.

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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