Resolve a free-text query to canonical FLOPS index slugs. Use when you don't know the exact slug — e.g. 'H100 spot' returns the matching SPOT family entries. Best paired with get_price to look up + quote a value in one turn.
| Name | Required | Description | Default |
|---|---|---|---|
| q | Yes | Free-text query (e.g. 'h100 spot' or 'b200 on-demand'). | |
| limit | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It explains the mapping behavior via example and mentions 'canonical' slugs, but lacks disclosure on edge cases (empty results, limit behavior, fuzzy matching). Core behavior is clear but not deeply transparent.
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?
Three sentences, front-loaded with purpose, then usage and pairing recommendation. No redundant or filler content; every sentence earns its place.
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 2-parameter search tool with no output schema, the description covers purpose, when to use, and paired tools. Missing details like empty-result behavior or limit semantics, but these are minor gaps given the tool's simplicity.
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 50%: q has a description with the same example, while limit has no semantic description. The tool description does not add new meaning for limit and repeats q's example, adding minimal value beyond the schema.
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 function with a specific verb ('Resolve') and resource ('free-text query to canonical FLOPS index slugs'). The example 'H100 spot' returns matching SPOT family entries, distinguishing it from siblings like list_indices or get_index.
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 says 'Use when you don't know the exact slug', providing a clear condition. Also recommends pairing with get_price for lookup+quote. It doesn't explicitly name alternatives (e.g., get_index when slug is known), but the context implies them.
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.
Each tool has a distinct primary purpose: discovery (list/search), pricing (get_price), citation (get_index), and verification (verify). There is slight overlap between get_price and verify in 'current value' lookup mode, but descriptions clarify intended use cases.
Most tools follow a consistent verb_noun pattern in snake_case (get_index, get_price, list_indices, search_indices). The tool 'verify' deviates by using a bare verb without a noun, breaking the pattern slightly.
Five tools is well-scoped for a data lookup and verification server. Each tool covers a distinct need without bloat, and the count is within the ideal range for a focused service.
The tool set covers the full lifecycle for interacting with FLOPS indices: discover (list/search), retrieve current price (get_price), retrieve citation metadata (get_index), and validate values (verify). No obvious gaps for the stated purpose, as advanced features like source-level detail are intentionally excluded.