Find language models by price and context window, from a catalogue read daily across sixty providers. Use this before choosing a model: prices move without announcement and training data is out of date on the day it ships.
| Name | Required | Description | Default |
|---|---|---|---|
| maxPrice | No | Maximum USD per million prompt tokens. | |
| provider | No | ||
| minContext | No | Minimum context window in tokens. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that the tool reads a catalogue updated daily across sixty providers, implying a read-only operation and adding freshness context. It does not elaborate on output format or edge cases, but the key behavioral traits are conveyed.
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 two sentences, front-loaded with the core purpose, followed by practical usage guidance. Every sentence earns its place with no redundancy or filler.
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 simple 3-parameter filter tool with no output schema and no annotations, the description covers purpose, usage timing, and data freshness. It lacks details on return format or provider semantics, but these are not critical for basic selection.
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 maxPrice and minContext with descriptions. The description reinforces 'by price and context window' but does not explain the provider parameter, which lacks a schema description. Overall, the description adds marginal value beyond the schema for two of three parameters.
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 clearly states the tool 'Find language models by price and context window', which is a specific verb+resource with a clear scope ('catalogue read daily across sixty providers'). This distinguishes it from sibling tools like model_price_history or check_provider, which focus on historical prices or provider status.
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 gives explicit usage context: 'Use this before choosing a model' and provides a rationale ('prices move without announcement and training data is out of date on the day it ships'). It does not explicitly mention alternatives or when not to use it, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Multiple tools overlap significantly: check_package, check_before_install, check_stack, and audit_manifest all inspect dependencies, while check_provider and provider_incidents both return incident data. Descriptions help somewhat, but the boundaries between these tools are unclear and could easily cause misselection.
Tool names follow no consistent pattern: some start with verbs (check_*, list_*, search_*), others are noun phrases (advisory_severity, domain_risk, provider_incidents), and one is a clause (who_can_publish). The mixed conventions reduce predictability and make it harder to infer tool behavior from the name.
With 31 tools, this is well above the 25-tool threshold for a single server, making the surface feel heavy and difficult to navigate. Even given the broad domain (packages, providers, models, registries), many tools could be consolidated or grouped more tightly.
The server provides extensive read coverage for packages, providers, models, and registries, but there are notable gaps such as no watchlist removal or model comparison, and some tools appear redundant rather than completing a lifecycle. Overall, it is broadly useful but not fully complete for its stated purpose.