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meshive-mcp

Official
by meshive

Delete Model

delete_model
DestructiveIdempotent

Delete a model registration after previewing it; call again with confirm=true to proceed. It fails while the model is still deployed.

Instructions

Delete a model registration. It fails while a serving of that model is still deployed. With confirm=false (default) it only returns the registration; call again with confirm=true after the user agreed. Every write requires operation_id. Reuse the ID returned by the preview, or generate a UUID before the first call. Keep it for confirmation and all retries; a new ID means a new operation. After a timeout, check operation_status and resource state before retrying.

Input Schema

NameRequiredDescriptionDefault
confirmNo
workspaceNo
operation_idNo
registration_idYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already declare destructiveHint=true and idempotentHint=true, so the description's job is to add the operational context, which it does: the dependency failure when a serving is deployed, the preview-then-confirm gate, and the timeout recovery path via operation_status. That is substantial beyond the structured hints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core action and its blocker, then the confirm flow, then the operation_id rules. Four dense sentences, all earning their place; the operation_id guidance is slightly repetitive but not wasteful.

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?

An output schema exists, so return shapes needn't be described. For a destructive open-world operation, the guidance covers the confirmation gate, dependency failure, and retry semantics. It stops short of stating permission requirements or how workspace selection changes the target, which for a multi-tenant delete is a real residual gap.

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 0%, so the description must carry the load. It explains confirm (default false) and the reuse/new-operation semantics of operation_id thoroughly, but says nothing about registration_id (the only required parameter) or workspace scoping. Half the parameters remain undocumented in both places.

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 and resource ("Delete a model registration") and immediately distinguishes it from a nearby sibling concern by noting it fails while a serving of that model is deployed — separating it from delete_serving. An agent can tell what this removes without opening the schema.

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

Usage Guidelines5/5

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

The two-phase flow is spelled out explicitly: confirm=false (default) only previews, confirm=true performs the delete only after user agreement. It also names the alternative for checking state (operation_status) and prescribes retry behavior, leaving nothing to inference.

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