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Samuraizer

Samuraizer

by UladzKha
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Summarize Transcript

summarize_transcript

Transform meeting transcripts into concise summaries. Extract key decisions, action items, and discussion points to save time and improve follow-up.

Instructions

Generate a concise meeting summary from transcript text.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "transcriptText": "<transcriptText>"
    },
    "name": "summarize_transcript"
  }
}

Input Schema

NameRequiredDescriptionDefault
modelNoOllama model to use (optional)
transcriptTextYesFull transcript text to summarize

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.6

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries full behavioral disclosure burden. It states the tool 'generates' a summary, which implies a read-only LLM operation, but it does not mention that an LLM is used, whether the operation is asynchronous, what the output format is, or any errors/limits. The description is too sparse to convey behavioral expectations.

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?

A single, efficient sentence that is front-loaded and contains zero filler. All words carry meaning, and the description is appropriately sized for a simple tool.

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

Completeness2/5

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

While the tool is simple with only 2 parameters, the description lacks essential contextual information: it doesn't describe the output format, how the 'model' parameter affects behavior, what happens with very long transcripts, or whether it is an offline operation. With no output schema and no annotations, the description should compensate but doesn't.

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 coverage is 100%, meaning both parameters (transcriptText, model) are documented in the schema itself. The description adds no additional semantic detail beyond what the schema provides—it only mentions the overall function. Baseline 3 is appropriate since the schema carries the semantic weight.

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 description states a clear verb+resource: 'Generate a concise meeting summary from transcript text.' This distinguishes it from sibling tools like extract_action_items and extract_decisions, which produce specific output types rather than an overall summary. However, it doesn't explicitly contrast with those siblings, so a 5 is not warranted.

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

Usage Guidelines2/5

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

No guidance is given on when to use this tool versus alternatives such as extract_action_items, extract_decisions, or get_meeting. The description only says 'from transcript text' but does not mention prerequisites, when a summary is appropriate, or when a different tool should be chosen. There is no when/when-not guidance.

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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