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Samuraizer

Samuraizer

by UladzKha
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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Process Recording

process_recording

Process an audio recording through transcription and analysis to extract a meeting summary, action items, decisions, and output file paths.

Instructions

Run the full Samuraizer pipeline on an audio file. Returns summary, action items, decisions, and output file paths.

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": {
      "filePath": "<filePath>"
    },
    "name": "process_recording"
  }
}

Input Schema

NameRequiredDescriptionDefault
modelNoOllama model to use (optional)
filePathYesAbsolute path to the audio file

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.6

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It says the tool runs a pipeline and returns output file paths, hinting at file creation, but it does not disclose whether the operation is long-running, synchronous, resource-intensive, or whether intermediate artifacts are retained or cleaned up. This is a meaningful gap for a multi-stage processing tool.

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 single, front-loaded sentence with no filler. It names the action, the resource, and the key return values without repeating schema information. Every part earns its place.

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?

For a tool with no output schema and no annotations, the description names the expected outputs and identifies the main input, which is helpful. However, it omits practical context such as how long processing may take, what happens after output files are written, and how to choose between this orchestration tool and the more granular sibling tools. The definition is adequate but leaves several gaps for autonomous agents.

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 100%: filePath is described as 'Absolute path to the audio file' and model as 'Ollama model to use (optional)'. The description itself adds no parameter-specific meaning, but the baseline of 3 applies because the schema already documents both parameters adequately.

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 pair: 'Run the full Samuraizer pipeline on an audio file.' It also enumerates the outputs (summary, action items, decisions, output file paths), making its scope distinct from the individual sibling tools. It does not explicitly name a sibling to contrast with, but 'full pipeline' differentiates it sufficiently.

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?

The phrase 'full pipeline' plus the enumerated outputs implies this is the end-to-end tool to use when all processing results are needed at once. However, it does not explicitly say when to prefer it over normalize_audio, transcribe_audio, summarize_transcript, or the extraction tools, nor does it state any exclusion conditions.

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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