What to switch to when a model is gone or you need a fallback. Ranked by closeness in measured performance, not by vendor or price: what you usually need to preserve first is the quality of the output. Candidates whose context window is less than half the original are excluded. Returns the score, price and context deltas so you can judge; we do not pick for you.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | OpenRouter id or Hugging Face repo id |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does so well: it discloses the ranking criterion (performance closeness), the exclusion rule (context window less than half the original), the returned fields (score, price, context deltas), and that the tool does not make the decision for the user.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three dense sentences with no filler. It front-loads the purpose, then explains ranking logic, exclusion criteria, and output contents in a logical order.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with no output schema and no annotations, the description covers why to use it, how results are ranked, what is excluded, and what is returned. An agent has enough information to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents the id parameter at 100%, and the description adds context that this id represents the original/gone model to be replaced. This clarifies the role of the parameter beyond the schema's type-level description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific purpose: find a replacement or fallback when a model is gone. It also distinguishes itself from sibling tools like search_models or compare_models by focusing on substitution rather than general discovery or comparison.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It clearly identifies when to use the tool ('when a model is gone or you need a fallback'), giving the agent a concrete trigger. It does not explicitly name sibling alternatives or state when not to use it, but the usage context is unambiguous.
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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