seat-intelligence

rowhint_help_me_pick

Conversational seat picker. Asks the user a few structured questions (flight, route length, what they care most about, cabin class), then returns the top 3 seat recommendations with notes. Use this when someone wants help choosing but hasn't specified a seat or even which aircraft — the tool walks them through it via elicitation.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`flight`	No	Optional flight number. If omitted, the tool will elicit it from the user.

TDQS

A4.2/5.0

Behavior3/5

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

No annotations provided, so description carries full burden. Mentions elicitation and returns top 3, but lacks details on side effects (e.g., read-only) or handling of ambiguous inputs.

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?

Single, front-loaded sentence with no redundancy. Every word serves a purpose.

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 it's a conversational tool, description adequately covers input, process, and output format. No output schema but mentions 'top 3 seat recommendations with notes'.

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?

Only one parameter (flight) with full schema description coverage. Description reinforces that if omitted, tool will elicit, adding value beyond schema.

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?

Description clearly states it is a 'conversational seat picker' that asks structured questions and returns top 3 recommendations, distinguishing it from siblings like rowhint_pick_seat which expects a specific seat.

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?

Explicitly says to use when user hasn't specified a seat or aircraft, providing clear context for when to use. Does not name alternatives but sibling list exists.

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

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