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Glama

esxi_transfer_start

Destructive

Start background streaming datastore, guest, or NFC download/upload transfers up to 64 TiB; returns a job ID immediately for status checks and chunked retrieval.

Instructions

后台流式 datastore/guest/NFC 下载或上传(最多64TiB显式上限,受暂存磁盘空间约束)。立即返回 job_id,status 查询,read_chunk 分块取回。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYes
pathNo
leaseNo
dry_runNo
datastoreNo
max_bytesNo
operationYes
overwriteNo
request_idNo
source_urlNo
http_methodNoPUT
content_typeNoapplication/octet-stream
transfer_urlNo
source_job_idNo
expected_sha256No

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare destructive=true, readOnly=false, and non-idempotent, so the description is not burdened with safety disclosure. It adds meaningful operational context: the transfer runs in the background, returns a job_id immediately, has a 64TiB upper bound, and is constrained by staging disk space.

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?

Two sentences, both front-loaded and free of filler. The first sentence states the core operation and constraints; the second states the return value and follow-up actions.

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?

Annotations and an output schema cover safety and return structure, and the description adds async job semantics plus size/staging constraints. However, for a 15-parameter mutation tool with 0% schema description coverage, the definition does not provide enough parameter-level detail to guide invocation confidently.

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% across 15 parameters, so the description must compensate. It only hints at kind/operation through 'datastore/guest/NFC download or upload' and mentions a 64TiB limit, but leaves parameters like max_bytes, dry_run, lease, source_url, expected_sha256, and overwrite unexplained.

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 specific action (background streaming download/upload), resource types (datastore/guest/NFC), and the immediate outcome (returns job_id). It distinguishes itself from follow-up siblings by naming status query and read_chunk retrieval, though it does not explicitly say 'start' or contrast with esxi_datastore_transfer / esxi_api_transfer.

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?

It clearly implies the workflow: start here, then use status to query and read_chunk to retrieve data. This gives strong post-invocation guidance, but it does not state when to choose this tool over alternatives like esxi_datastore_transfer or esxi_api_transfer.

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