get_method_support

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

No annotations are provided, so the description carries the full burden. It mentions that data is 'auto-probed weekly,' providing insight into data freshness and caching behavior. It does not explicitly state side effects, but the tool is clearly read-only and the lack of destructive implications is implicit.

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 extremely concise, using a single sentence to convey purpose, usage, and examples. No unnecessary words or repetition; every phrase adds value.

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?

The description fully covers what the tool does, how to invoke it in both modes, and what kind of results to expect (overview or per-chain support). It is self-contained for an agent to use correctly without additional context.

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 has 100% coverage with a clear description for the optional 'method' parameter. The tool description additionally explains the semantics of omitting versus providing the parameter, enriching the parameter meaning beyond the schema alone.

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's purpose: reporting which JSON-RPC methods work on which chain. It provides specific examples and distinguishes it from sibling tools like list_chains and probe_endpoint by focusing on method support rather than chain listing or endpoint probing.

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?

Explicitly explains when to call without arguments (overview) versus with a method name (per-chain support). This gives clear, actionable guidance on how to use the tool effectively.

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