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Search real places in a destination

search_places
Read-onlyIdempotent

Find real, currently-operating places in a destination — restaurants, bars, beaches, spas, viewpoints, temples. Ranked by quality (rating weighted by how many reviews stand behind it). When near is a "lat,lng" coordinate pair, results are limited to about 5 km of that point, ranked by a blend of quality and distance — so a 4.8★ institution two streets away beats an unrated snack bar next door — and each carries distance_m. When near is a neighbourhood name it filters by area and NO distance is returned. Returns name, category, area, rating, review count, phone, address and opening hours where known. NEVER invents a place: if NUM does not hold it, it is not returned. You MUST display the returned attribution string wherever you show these results.

Input Schema

NameRequiredDescriptionDefault
nearNoA "lat,lng" pair (e.g. "7.8208,98.2976") for distance-ranked results, or a neighbourhood name to filter by area, e.g. "Kata Beach".
limitNoMax results, 1–20. Default 8.
queryNoFree text, e.g. "thai seafood", "rooftop".
categoryNorestaurant | bar | beach | spa | viewpoint | temple | waterfall | cafe (any case). Omit for all.
destinationYesDestination slug or city name, e.g. "phuket", "bangkok".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already cover read-only/idempotent/non-destructive/closed-world, and the description adds genuinely new behavioral facts: the ranking formula (rating weighted by review volume, distance blend), the exact field set returned, the guarantee that it never invents a place, and a hard obligation to display the `attribution` string. These are obligations an agent could not infer from structured fields.

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

Conciseness4/5

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

Front-loaded with purpose, then the two `near` modes, then the return contract and the attribution mandate — a logical order with no filler. The 4.8★/'unrated snack bar' illustration is slightly verbose, though it does convey the ranking blend efficiently.

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

Completeness5/5

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

With no output schema, the description carries the return contract and does so explicitly (name, category, area, rating, review count, phone, address, hours) plus the conditional `distance_m`. Combined with annotations covering safety and a fully documented schema, nothing an agent needs to call it correctly is missing.

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 earns above that by explaining the consequence of each `near` form (radius cap, distance_m presence/absence) and by clarifying the quality-vs-distance ranking tradeoff. `query` and `category` are left to the schema, but that is acceptable given full coverage.

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 ('Find real, currently-operating places in a destination') and enumerates the categories covered. It is clearly distinct from siblings like place_details or open_places, which are not described as destination-scoped search.

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

Usage Guidelines4/5

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

Gives concrete context for the two modes of `near` (coordinate → ~5 km, distance-blended ranking with `distance_m`; neighbourhood → area filter, no distance) so an agent knows which form to supply. It never names the sibling alternatives (place_details, get_reviews, open_places) or states when not to use this tool, so it stops short of a 5.

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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