Explore segments
exploreSegmentsExplore segments - Returns the top 10 segments matching a specified query.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| bounds | Yes | ||
| max_cat | No | ||
| min_cat | No | ||
| activity_type | No |
exploreSegmentsExplore segments - Returns the top 10 segments matching a specified query.
| Name | Required | Description | Default |
|---|---|---|---|
| bounds | Yes | ||
| max_cat | No | ||
| min_cat | No | ||
| activity_type | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and destructiveHint=false, so the read-only nature is covered. The description adds the 'top 10' result limit, which is useful behavioral context. However, it does not disclose other behavioral traits such as the meaning of min/max category filters or the required bounds parameter.
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 concise and front-loaded, with a single sentence that includes the tool name and a clear return value. There is no fluff or redundant information. While it is under-specified in terms of parameters, that is a completeness issue, not a conciseness issue.
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?
Given the tool has 4 parameters with no schema descriptions, no output schema, and sibling tools requiring differentiation, the description is insufficient. It lacks any sense of the query structure, optional filters, or how it differs from sibling tools. The description is too minimal to be considered complete for this complexity.
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 description coverage is 0%, so the description must compensate by explaining parameters. It does not: no meaning for bounds, max_cat, min_cat, or activity_type is provided. The phrase 'matching a specified query' is generic and gives no insight into how to construct the query using the 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 returns the top 10 segments matching a query, providing a specific action and resource. It distinguishes itself from sibling tools like getEffortsBySegmentId by focusing on exploration rather than specific segment details. However, 'specified query' is vague and does not specify what parameters constitute the query.
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?
No guidance is provided on when to use this tool versus alternatives. Sibling tools exist for segment efforts, clubs, and gear, but the description offers no comparison or exclusions. The usage context is only implied by the name, not explicitly stated.
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 targets a distinct resource and operation: segments, clubs, gear, athlete, routes, and stats. Even potentially similar tools like getEffortsBySegmentId and getSegmentEffortById are clearly differentiated by their descriptions (listing efforts vs. fetching a single effort).
All tool names follow a consistent camelCase pattern with a verb (get, explore) followed by a specific noun phrase. Names like getClubById, getLoggedInAthlete, and getStats are uniform and predictable, making it easy to infer their purpose.
With 13 tools, the server is well-scoped for a focused read-only API over Strava data. The count is within the ideal range and each tool covers a meaningful aspect of the domain without redundancy or bloat.
The tool surface covers several Strava domains (clubs, segments, gear, routes, athlete stats) but is missing any activity-related operations (e.g., list activities, get activity by ID) and all write operations. This creates notable gaps for a comprehensive Strava integration, though the read-only scope may be intentional.