Skip to main content
Glama

ass_import_srt

Import SubRip (.srt) subtitles as new ASS lines for Aegisub documents, handling decimal separators, multi-line blocks, encoding, and optional time offsets.

Instructions

Import a SubRip (.srt) file as new ASS lines.

Handles , and . decimal separators, multi-line blocks, CRLF and a UTF-8 BOM; multi-line subtitle bodies become \N hard breaks.

Args: path: the .srt file to read. doc_id: document to append to; the current one when omitted. style: ASS style for the imported lines. offset_ms: shift every imported line in time.

Returns {"doc_id", "path", "count", "indices": [<0-based indices>], "lines": [<dict>], "skipped": <blocks without a timestamp>, "style", "offset_ms"}. Snapshot-backed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
styleNoDefault
doc_idNo
offset_msNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does fairly well: it discloses parsing edge cases (comma/dot decimal separators, multi-line blocks, CRLF, UTF-8 BOM), the conversion rule (multi-line bodies become \N hard breaks), and the snapshot-backed/undoable nature. It omits permission or open-document requirements, but the behavioral disclosure is meaningfully richer than a bare verb.

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?

Purpose is front-loaded, then behavior, then args and returns in scannable sections. Every sentence earns its place, though the doubled backtick formatting adds minor visual noise.

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 moderately complex import tool, the description covers format handling, all params, and the return payload (even restating the output schema). The main residual gap is document-state prerequisites, but overall an agent has what it needs to call it correctly.

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%, so the description must compensate, and it does: all four parameters are explained with real meaning (path = file to read, doc_id = document to append to with current-when-omitted fallback, style = ASS style for imported lines, offset_ms = time shift). This is exactly the compensation the low coverage requires.

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 first sentence states a specific verb and resource: importing a SubRip (.srt) file as new ASS lines. It is unambiguous and distinguishable from siblings like ass_add_line/ass_add_lines, which create lines rather than import an external format.

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 naming the .srt source format, but there is no explicit when-to-use vs alternatives, no statement of prerequisites (e.g. must a document be open / is ass_new_document required first), and no guidance on when importing is preferred over manual line creation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

Other Tools