Recommend a route tier (cheap / balanced / fast) for one JSON-RPC call from measured data: the method's weight, our probes' p50 on public and premium supply for the chain, and what each tier costs. No authentication required.
| Name | Required | Description | Default |
|---|---|---|---|
| need | No | cheap | balanced | fast — what matters most (default: let the measurement decide) | |
| chain | Yes | Chain slug, e.g. eth_mainnet | |
| method | Yes | JSON-RPC method, e.g. eth_call |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It usefully states that authentication is not required and describes the data sources (probes, costs), which indicates a non-mutating recommendation. It does not, however, disclose return shape, failure behavior, or whether any state changes occur beyond the recommendation.
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 main purpose is front-loaded in the first clause, and the rest is a compact list of the data inputs that justifies the recommendation. The separate 'No authentication required' sentence is useful and not redundant. No filler or repetition.
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 recommendation tool, the description covers purpose, key inputs, decision basis, and auth requirements well enough for an agent to invoke it. It could be slightly more complete by stating the output object shape, but 'recommend a route tier' already signals the primary return value.
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?
Schema coverage is 100%, so the baseline is 3. The description adds some context by naming the measured inputs (method weight, p50 on public/premium supply, costs) and matching the 'need' values, but it does not add invocation-level detail beyond the schema for chain, method, or need.
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 action ('Recommend a route tier'), the exact value space (cheap / balanced / fast), and the scope (one JSON-RPC call). This makes it clearly distinct from sibling tools like pick_chain, which chooses a chain rather than a tier.
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 implies the tool is for choosing a route tier for a single JSON-RPC call using measured data, and notes that no auth is needed. However, it never explicitly states when to use pick_route instead of pick_chain or when not to use it, so the usage guidance is only implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.