Skip to main content
Glama

로컬 음성 인식(ASR) 설치 시작

asr_install
Idempotent

Starts a resumable background install of the local Qwen3-ASR runtime for transcribe_vod, downloading and SHA-256-verifying files in ~/.cache/dotbugi-mcp/asr; track progress with asr_status.

Instructions

transcribe_vod 가 쓰는 로컬 음성 인식(Qwen3-ASR) 런타임을 ~/.cache/dotbugi-mcp/asr 에 설치하는 백그라운드 작업을 시작하고 바로 돌아온다. 수 GB 를 받으며 모든 파일은 코드에 고정된 sha256 으로 검증한다. 진행은 asr_status. 중단돼도 다시 부르면 이어 받는다.

Input Schema

NameRequiredDescriptionDefault
gpuNoNVIDIA GPU(Linux·WSL) 런타임. uv 가 필요하다
modelNo모델 (기본 0.6b). 1.7b 는 gpu 와 함께만

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.5/5.0
Behavior5/5

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

Goes well beyond the annotations: it discloses that this is an asynchronous background job that returns immediately, that it downloads several GB, that every file is verified against a hard-coded sha256, and that the operation is resumable. These are exactly the behavioral traits an agent needs but cannot derive from readOnlyHint/idempotentHint alone.

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?

Four compact sentences with zero filler: purpose and async nature first, then download/verification size, then progress tracking and resumability. Every sentence carries load-bearing information.

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?

With no output schema, the description still tells the agent that the call returns immediately and that progress must be polled via asr_status, which is the critical return-behavior detail. Combined with the fully documented params and annotations, nothing needed to call it correctly is missing.

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%, and the schema already documents both the gpu and model parameters including the uv requirement and the 1.7b-with-gpu constraint. The description adds no parameter-level meaning beyond that, so the baseline 3 applies.

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?

States a specific verb (install/start background job), the exact resource (the Qwen3-ASR runtime used by transcribe_vod), and the install location (~/.cache/dotbugi-mcp/asr). It is clearly distinguishable from siblings like asr_status and asr_remove.

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?

Explains that progress is tracked via asr_status and that re-calling resumes an interrupted install, which gives the agent clear post-call handling. It does not explicitly state when not to use it (e.g., if already installed) or name asr_remove as the counterpart, so it stops short of full routing guidance.

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