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Is this model deprecated, and what replaces it?

check_model_deprecation
Read-onlyIdempotent

Check whether one LLM model id is active, deprecated, or retired, plus its shutdown date and replacement, from that provider's deprecation page (OpenAI, Anthropic, Google, and other tracked LLM vendors). Use before hard-coding or calling a model, or when a call fails with model-not-found. Not for API uptime (check_api_status) and not for a retirement feed (list_recent_api_changes with kind model_retirement, or get_digest). Returns summary, verdict (active|deprecated|retired|unknown), recommended_action (keep_using|plan_migration|switch_now|verify_with_provider), replacement, shutdown_date, evidence, and freshness; pages are re-read every few hours. An unlisted id is verdict unknown, not an error; longer than 120 characters returns 400 bad_model_id. Example: {"model":"gpt-4-0613"}. Free within the daily quota, then $0.003 via x402. Alias: get_model (param id).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoDeprecated alias of model, only for the get_model tool name. Same 1–120 character API id. Ignored when model is also set.
modelNoExact API model id, not a display name or provider id. 1–120 characters; lowercased, and a leading models/ is stripped. Examples: gpt-4-0613, claude-3-opus-20240229, gemini-1.5-pro.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed6 schema fields changed
    • changedInput schema / properties / id / description
      Previous value: -"Deprecated alias of model."New value: +"Deprecated alias of model, only for the get_model tool name. Same 1–120 character API id. Ignored when model is also set."
    • addedInput schema / properties / id / maxLength
      Added value: +120
    • addedInput schema / properties / id / minLength
      Added value: +1
    • changedInput schema / properties / model / description
      Previous value: -"Model id as used in the API call. Examples: gpt-4o, claude-3-opus-20240229, gemini-1.5-pro."New value: +"Exact API model id, not a display name or provider id. 1–120 characters; lowercased, and a leading models/ is stripped. Examples: gpt-4-0613, claude-3-opus-20240229, gemini-1.5-pro."
    • addedInput schema / properties / model / maxLength
      Added value: +120
    • addedInput schema / properties / model / minLength
      Added value: +1
  2. Added

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/openWorld/safe. Beyond that, the description discloses freshness (re-read every few hours), unlisted-id semantics (verdict unknown, not an error), the 120-char 400 bad_model_id behavior, quota/pricing, and returns. Very transparent, though freshness granularity and rate-limit details beyond quota are thin.

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 purpose followed by usage, exclusions, returns, and edge cases. Dense but well organized; pricing/alias tail slightly crowds an otherwise tight description.

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?

No output schema, yet the description enumerates the return fields (summary, verdict, recommended_action, replacement, shutdown_date, evidence, freshness) and covers error semantics, freshness, and cost. 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 coverage is 100%, documenting id/model aliasing, normalization (lowercasing, models/ prefix stripped), and that display names are invalid. The description adds essentially nothing the schema does not already state; 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+resource (check whether a model id is active/deprecated/retired) and names the data source (provider deprecation pages). It explicitly distinguishes itself from siblings check_api_status and list_recent_api_changes/get_digest.

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?

Gives explicit when-to-use triggers ('before hard-coding or calling a model', 'when a call fails with model-not-found') and explicit exclusions with named alternatives for API uptime and retirement feeds.

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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