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Lodging Decision

by io.github.scenicstay

Lodging Decision

lodging_decision

Ranks caller-supplied lodging candidates for a traveler/trip and returns a deterministic, evidence-backed recommendation with score breakdown, tradeoffs, risk flags, missing information, and confidence.

SCOPE (alpha, non-sensitive categories only): budget, location, amenities, quality/reviews, cancellation policy, fees, remote-work and family and business/relocation/event trip framing, and stated accessibility needs. This tool does NOT accept, infer, or act on race, color, national origin, religion, sex, gender identity, sexual orientation, familial status, or any other protected characteristic or Safety & Belonging signal -- requests containing such content in free-text fields are rejected, not silently filtered.

This tool does not search inventory (you must supply candidate_listings), does not book or transact, and does not persist any data. It is unauthenticated, unversioned, alpha-quality: recommendations are deterministic given identical input but are not calibrated against real human booking outcomes. Always re-verify availability, price, and policy before booking.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tripYes
travelerYes
candidate_listingsYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

With no annotations, the description compensates thoroughly: it discloses deterministic behavior, rejection of protected-characteristic content, no persistence, alpha quality, and unauthenticated operation. It also details the output components.

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?

The description opens with a crisp summary of what the tool does, then layers scope, exclusions, and caveats in a logical order. No wasted words; each sentence conveys necessary context.

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?

The description covers functionality, scope, exclusions, output components, and limitations. Given the complex nested schema and lack of annotations, it provides sufficient context for an agent to decide when to call the tool and what to expect, though it could be more explicit about error handling or edge cases.

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?

Schema description coverage is 0%, so the description carries the burden. It clarifies that candidate_listings are caller-supplied and outlines the decision scope (budget, location, amenities, etc.), but does not detail the meaning or constraints of individual parameters beyond what their names imply in the schema. Partial compensation.

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?

The description clearly states the tool ranks caller-supplied lodging candidates and returns a deterministic, evidence-backed recommendation with score breakdown, tradeoffs, risk flags, missing information, and confidence. It explicitly distinguishes itself from search, booking, and persistence tools.

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?

The description explicitly states the tool does not search inventory, book, or persist data, making clear the user must supply candidate_listings. It also sets expectations for alpha quality and verification before booking, though it doesn't name alternative tools.

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

All Lodging Decision toolsInspect
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TDQS

A4.4/5.0
Disambiguation5/5

With only one tool, there is no possibility of confusion or misselection. The tool's purpose is clear and distinct.

Naming Consistency5/5

The single tool name uses a clear snake_case format and is self-descriptive. There are no other tools to create inconsistency.

Tool Count3/5

One tool feels thin for a server; the functionality is broad but could logically be split into separate concerns (e.g., scoring, risk assessment). It is borderline but not unreasonable.

Completeness5/5

For its stated purpose of ranking lodging candidates and providing evidence-backed recommendations, the tool covers all necessary aspects: scoring, tradeoffs, risk flags, and missing information. It explicitly excludes search and booking, which are outside its scope.

Resources