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Search routes

search_routes
Read-onlyIdempotent

Search Skamper's curated UK running-route database when the user gives concrete filters — name, location (lat/lng), distance range, max ascent, paved surface %, course shape, or national park. Returns up to 20 compact route summaries with canonical URLs. If the user instead describes who they are or what they want ('I'm a trail runner who hates roads'), prefer recommend_route. For parkrun-distance asks, prefer find_5k.

Input Schema

NameRequiredDescriptionDefault
limitNo
queryNoFree text — searches route titles and slugs. Optional.
near_latNoLatitude to search near. Pair with near_lng.
near_lngNoLongitude to search near. Pair with near_lat.
course_shapeNo
max_ascent_mNoMaximum total ascent in metres (flatter routes).
max_paved_pctNoMaximum paved surface % (trail runners).
min_paved_pctNoMinimum paved surface % (road runners).
national_parkNoFilter to routes in this national park (name or slug).
max_distance_kmNo
min_distance_kmNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint=false, so the safety profile is covered. The description adds value beyond that by disclosing the result cap ('up to 20 compact route summaries') and the return shape ('canonical URLs'). It does not say what happens with zero matches or how limit interacts with the cap, so it stops short of a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, all load-bearing: capability and filters first, return shape second, disambiguation third. No repetition of the title and no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an 11-parameter, zero-required search tool with no output schema, the description covers the filter space, the result size, and routing to siblings. It omits edge behavior such as empty results and whether filters combine as AND, which keeps it from being fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 64% schema coverage the schema already documents most parameters, including the runner-oriented hints on max_paved_pct and min_paved_pct. The description's enumeration of filter dimensions largely mirrors those schema properties rather than adding new semantics; the only mild addition is framing 'name' as a filter, while the schema calls the parameter 'query' and describes it as free text over titles and slugs.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Search Skamper's curated UK running-route database') and enumerates the concrete filter dimensions it accepts (name, lat/lng, distance range, max ascent, paved %, course shape, national park). It also names the sibling tools it is not (recommend_route, find_5k), so an agent can route correctly without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit triggering condition — use when the user gives concrete filters — plus two named alternatives with the exact condition that selects each ('describes who they are or what they want' → recommend_route; 'parkrun-distance asks' → find_5k). Both when-to-use and when-not-to-use are covered.

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

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