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dezer32

openwhispr-mcp

by dezer32

Read a note transcript

get_note_transcript
Read-only

Retrieve a recorded note's transcript as diarized segments, timestamped text lines, or per-speaker totals. Filter by speaker or audio source, and page through long recordings.

Instructions

Read a note's transcript. format=segments pages diarized segments with times relative to the recording start (offset/limit, speaker/source filters); format=text renders "[mm:ss] speaker: …" lines; format=speakers gives per-speaker totals only — use it first on long recordings. A note with no transcript returns an empty result, not an error.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoformat:"segments" only. Segments (or text chunks) per page, 1-200. Default 100.
formatNosegments: one entry per diarized segment, paged. text: [mm:ss] speaker lines. speakers: per-speaker totals only.segments
offsetNoformat:"segments" only. First segment (or text chunk) to return. Default 0.
sourceNoKeep only microphone or system audio.
note_idYesNote id from list_notes, search_notes or get_note.
speakerNoKeep only this speaker; matches the raw key (speaker_0, you) or the resolved label.
expect_updated_atNonote_updated_at from the previous page. Fails with transcript_changed if the note moved, because offset paging would then skip or duplicate segments.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

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

Annotations declare readOnlyHint=true, and the description adds substantial behavior beyond that: pagination semantics, relative timestamps, format-specific output shapes, speaker/source filters, and the important fact that a missing transcript returns an empty result rather than an error. This strongly supports correct invocation and interpretation.

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 a compact, well-structured paragraph with no filler. It leads with the purpose, then enumerates the three formats and the key edge case. Every clause adds information an agent needs.

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

Completeness5/5

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

For a read-only tool with 7 parameters and no output schema, the description is sufficiently complete: it explains the main return formats, the pagination/filtering behavior, the long-recording recommendation, and the empty-result case. Parameter constraints are already covered by the schema, so nothing critical is missing.

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

Parameters4/5

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

The input schema already documents all 7 parameters with 100% coverage, so the baseline is 3. The description adds meaningful context beyond the schema by explaining what each format produces, that speakers totals are intended as an initial summary, and that offset/limit apply to segment pages. This is a clear bonus over 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 states a specific verb and resource: 'Read a note's transcript.' It further explains the three output formats, making clear what the tool returns and distinguishing it from metadata-focused siblings like get_note. The purpose is not tautological and is immediately understandable.

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

Usage Guidelines4/5

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

The description gives clear contextual guidance, especially for format=speakers ('use it first on long recordings') and for the empty-result case. It does not explicitly compare against get_transcription or other siblings, but the intended usage is clear enough from the wording.

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