Skip to main content
Glama

transcript_search

Search a transcript by phrase and get timestamps, even while transcription runs; fuzzy matching helps when you only remember part of the wording.

Instructions

Find a phrase in a transcript, with timestamps.

The intended way into a long transcript, together with transcript_segments — pulling the whole thing would flood your context. Works on a running job: it searches what has been committed so far. Falls back to fuzzy matching when nothing matches whole words, which is what helps when you half-remember a phrase.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
job_idYes
max_resultsNo
context_secondsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and does disclosing meaningful traits: it works on a running job and only searches previously committed content, and it falls back to fuzzy matching when exact words fail. It does not state read-only/safety posture or rate/limit behavior, but the read nature is strongly implied by 'find'.

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?

Front-loaded with the core action in the first sentence, then behavior and rationale in short paragraphs. Every sentence adds information; nothing is filler.

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?

Output schema exists, so return values need not be described. The description covers purpose, use context, and runtime behavior (running jobs, fuzzy fallback), leaving only the underdocumented optional parameters as a gap.

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 description coverage is 0% for all four parameters, so the description must compensate and largely does not. It hints at query semantics ('phrase') and timestamps (mapping loosely to context_seconds), but says nothing about max_results or how context_seconds bounds the returned window.

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?

States a specific verb+resource ('find a phrase in a transcript') plus a key output trait (timestamps). It names transcript_segments as a companion but does not distinguish itself from other search-adjacent siblings such as transcript_find_clips or transcript_get.

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?

Gives clear context for use: it is 'the intended way into a long transcript' alongside transcript_segments, with the rationale that pulling the whole transcript would flood context. It names an alternative but offers no explicit when-not-to-use or exclusions (e.g., versus transcript_find_clips).

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