Skip to main content
Glama

delete_integration_model

Destructive

Removes a custom model from a Portkey integration; built-in models should be disabled instead because deletion applies only to custom entries.

Instructions

Delete a custom model from an integration. Built-in models should be disabled instead, because deletion only applies to custom entries. Returns success after the custom model is removed.

Input Schema

NameRequiredDescriptionDefault
slugYesThe slug of the integration
model_slugYesThe slug of the model to delete

Output Schema

NameRequiredDescriptionDefault
okYesWhether the tool call succeeded and returned structured data
dataNoStructured success payload when ok is true
errorNoStructured error payload when ok is false

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.0.9
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • changedOutput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. Addedv1.0.1
  3. Removed
  4. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true and idempotentHint=false, so the safety profile is covered; the description adds the non-obvious constraint that only custom models are eligible and that success is returned once removal completes. It stops short of stating that the call fails on built-in models or repeated deletes.

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?

Three short sentences, front-loaded with the action and the primary exclusion, with no redundant restatement of the tool name.

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 and annotations carry the destructive/non-idempotent profile, so the description only needs the domain constraint, which it supplies. Missing only the failure mode (built-in model rejection) and irreversibility wording.

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 both parameters (slug, model_slug) are documented there, so the description adds no parameter-level meaning beyond naming the integration and the model. Baseline 3 applies when the schema does the heavy lifting.

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 custom model from an integration') and immediately bounds the scope to custom entries, which distinguishes it from the sibling update_integration_models path used to disable built-ins. An agent can identify the target object and the exact effect 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 Guidelines4/5

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

Explicitly gives a when-not-to-use rule: built-in models should be disabled instead because deletion only applies to custom entries. It does not name the concrete sibling tool that performs the disable, so the agent must infer the alternative, but the decision boundary itself is unambiguous.

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

Deploy Server

Other Tools