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rowhint_get_seat_score

Get the quality score (1-10), color rating, and detailed notes for a specific airline seat. Returns comfort assessment, recline data, proximity warnings, and window alignment issues. Use when someone asks "Is seat 14A good on the Delta 737-800?" or wants to know about a specific seat before booking.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seatYesSeat identifier — row number + letter (e.g., 21A, 3F, 45K)
config_idYesAircraft configuration ID (e.g., DL-738, UA-77W). Get valid IDs from rowhint_get_config_overview.

TDQS

A4/5.0
Behavior3/5

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

No annotations exist, so the description carries the full burden. It lists return contents (comfort assessment, recline data, etc.) but does not disclose whether the operation is read-only, has authentication requirements, or side effects. The description is adequate but could explicitly state safety and read-only behavior.

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 sentences with no wasted words. The first sentence states function and return contents; the second gives a concrete use case. Efficient and well-structured.

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 two simple parameters, no output schema, and no annotations, the description provides sufficient context to understand the tool's purpose and expected input. It lacks explicit output structure but covers key information categories. It is largely complete for its complexity.

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 100%, so baseline is 3. The description adds no further meaning to the parameters beyond what the schema descriptions already provide ('seat' and 'config_id' are clearly defined in schema). Thus it does not enhance parameter understanding.

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 has a specific verb ('Get') and resource ('quality score... for a specific airline seat'). It lists specific return contents and distinguishes from sibling tools like rowhint_get_best_seats and rowhint_compare_seats by focusing on a single seat's detailed evaluation. The concrete example reinforces purpose.

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 when to use it: when someone asks about a specific seat's quality or wants to know before booking. While it doesn't list when not to use or provide alternative sibling names, the usage scenario is clear and contextually appropriate.

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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TDQS

A4/5.0
Disambiguation4/5

Tools are mostly distinct, with clear purposes like comparing seats, getting best seats, overview, score, windowless, etc. Slight overlap between get_best_seats and pick_seat, as both recommend seats but for different contexts (config vs. flight). Otherwise, each tool has a unique role.

Naming Consistency4/5

All tools use the 'rowhint_' prefix and snake_case verb_noun pattern. Most are consistent (e.g., get_*, compare_*, pick_*), but 'help_me_pick' and 'seat_roast' break the pattern slightly with imperative phrases or noun-verb order. Overall, naming is clear and predictable.

Tool Count5/5

With 8 tools, the server covers a reasonable scope for seat intelligence: overview, recommendations, specific seat info, comparison, and a conversational picker. The count is well-balanced, not too few or too many for the domain.

Completeness4/5

Core use cases are covered: best seats, specific seat scoring, comparison, windowless seats, and flight-based picks. Minor gaps include lack of a tool to list all seats on a config with full details, but the conversational picker and overview tool mitigate this. Overall, agents can accomplish key tasks without dead ends.

Resources