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LLMIntel Model Lifecycle

LLMIntel Model Lifecycle

by hivemindunit
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

Suggest a replacement for a model

suggest_replacement
Read-only

Find recommended replacements for a deprecated or retiring model, or discover active models from the same provider.

Instructions

Given a deprecated or retiring model, return the provider's recommended replacement(s) and, when none is published, active models from the same provider to consider.

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": {
      "model": "<model>"
    },
    "name": "suggest_replacement"
  }
}

Input Schema

NameRequiredDescriptionDefault
modelYesModel id or alias to find a replacement for.

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?

The description discloses the behavior beyond annotations: it returns recommended replacements when available, and falls back to active models from the same provider. This adds value over the annotations (readOnlyHint, openWorldHint) and is fully transparent.

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, well-structured sentence that is front-loaded and contains no unnecessary words. Every part is essential.

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?

For a simple tool with one parameter and no output schema, the description explains the return value clearly (replacement(s) or active models). No additional context is needed.

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 input parameter description is adequate. The tool description does not add further details about the parameter format or examples, so it meets the baseline but does not exceed it.

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?

The description clearly states the action (suggest replacement), the resource (deprecated/retiring model), and the fallback behavior (returning active models from the same provider). It effectively distinguishes from sibling tools like list_retiring_models and check_model.

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?

The description clearly indicates when to use the tool: when a model is deprecated or retiring. However, it does not explicitly state when not to use it or mention alternative tools for other scenarios, but the context is sufficiently clear.

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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