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Find Similar Campgrounds

find_similar_campgrounds
Read-only

Find campgrounds similar to a given campground using vector embedding similarity.

Uses pre-computed embeddings combining review text (semantic) and structured attributes (amenities, terrain, activities) for nuanced similarity matching.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
result_limitNoNumber of results (1-50, default 20)
campground_idYesCUID of the target campground to find similar ones for
max_distance_kmNoOptional max distance in km (omit for nationwide search)
semantic_weightNoWeight for text/review similarity (0-1, default 0.6)
structured_weightNoWeight for attribute similarity (0-1, default 0.4)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed6 schema fields changed
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / campground_id / description
      Added value: +"CUID of the target campground to find similar ones for"
    • addedInput schema / properties / max_distance_km / description
      Added value: +"Optional max distance in km (omit for nationwide search)"
    • addedInput schema / properties / result_limit / description
      Added value: +"Number of results (1-50, default 20)"
    • addedInput schema / properties / semantic_weight / description
      Added value: +"Weight for text/review similarity (0-1, default 0.6)"
    • addedInput schema / properties / structured_weight / description
      Added value: +"Weight for attribute similarity (0-1, default 0.4)"
  2. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so safety and scope are clear. The description adds meaningful behavioral context beyond annotations: it explains that similarity is computed from pre-computed embeddings combining review text and structured attributes, which helps the agent interpret results.

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?

Two tightly written sentences with zero waste. The core purpose is front-loaded, and the second sentence adds useful mechanism without padding.

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?

Given the read-only annotations, full output schema, and complete parameter descriptions, the definition is nearly self-sufficient. The main gap is the absence of sibling differentiation against search_campgrounds, which slightly hinders tool selection despite the otherwise complete picture.

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

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3. The description adds conceptual meaning to the semantic_weight and structured_weight parameters by explaining that embeddings combine review text (semantic) and structured attributes (amenities, terrain, activities), clarifying what those weights control beyond the schema's terse descriptions.

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

Purpose4/5

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

The description states a specific verb (Find) and resource (campgrounds similar to a given campground), and adds the method (vector embedding similarity). It distinguishes itself from a generic search by requiring a target campground, but does not explicitly name the sibling search_campgrounds to sharpen the contrast.

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

Usage Guidelines2/5

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

The description gives no guidance on when to use this tool versus alternatives like search_campgrounds. There are no exclusions, conditions, or named alternatives; the agent must infer usage entirely from the purpose statement.

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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