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Request a seat at a Yerevan Product Coffee table

request_table_seat
Idempotent

Ask for one of the five guest seats at a Yerevan Product Coffee table. Call list_upcoming_tables first and pass one of its exact startsAt values. This sends a real request to a real person, so it takes two calls: call it once to see exactly what would be sent, show that to the person it is about, then call it again with the same values and confirm: true. A request is not a booking — Hovhannes reads each one himself and replies within 3–5 days, and no seat is held until he does.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailYesTheir email address. The reply and the confirmation both go here, so it has to be one they read
phoneYesTheir phone number with its country code, like +374 11 22 33 44. Used only on the evening itself and deleted if the request is closed
confirmNoLeave unset or false to validate and preview without sending anything. Set to true only after the person has seen the preview and agreed to it
buildingNoWhat they are building, in their own words. Optional but read
fullNameYesThe applicant's full name, as they would write it
eventStartYesWhich table. The exact `startsAt` from list_upcoming_tables is best, but the calendar day on its own ("2026-09-10") or the word "next" also resolve against the real schedule
motivationNoWhy this table, now. Optional
linkedinUrlYesTheir personal LinkedIn profile URL (linkedin.com/in/…). Required: seats are chosen on who sits together, which cannot be judged from a name. Company pages, posts and shortened links are refused
perspectiveYesThe perspective they bring: founder (Building or validating a product of your own.); product (Deciding scope, priority, discovery, and delivery.); design-research (Bringing users, flows, and evidence into the room.); engineering (Turning product intent into something real.); growth (Positioning, demand, distribution, retention.); customer (Sales, support, and discovery signals.); hybrid-other (More than one lens, and that is fine.)
contributionNoWhat they can offer the other five people. Optional
discussionQuestionNoThe one real decision or trade-off they are stuck on and want the table's help with. Optional, and the single most useful thing to include

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableNo
statusNo
messageNo
duplicateNo
submittedYes
dailyLimitNo
willSubmitNo
instructionNo
privacyNoteNo
alreadyRequestedNo
needsConfirmationNo
whatHappensOnConfirmNo
confirmationEmailedToNo
confirmationEmailStatusNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

The description discloses that the call 'sends a real request to a real person,' which goes beyond the readOnlyHint=false annotation by explaining the human side effect. It also explains the dry-run vs confirmed behavior, manual review by Hovhannes, and the 3–5 day delay, none of which the annotations convey.

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?

Four sentences cover purpose, prerequisite, workflow, and expectations without repetition. The most actionable instructions ('Call list_upcoming_tables first') are front-loaded, and no sentence is filler.

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?

For a tool with 11 parameters, a two-call confirmation workflow, and human async review, the description covers the essential operational context: what to do first, what the first vs second call does, and what outcome to expect. An output schema exists, so return-value details are not required here; nothing an agent needs to invoke this correctly is missing.

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 coverage is 100%, and the schema descriptions already provide detailed guidance for every parameter, including eventStart resolution and confirm semantics. The tool description reinforces 'pass one of its exact startsAt values' and 'confirm: true' but adds no new per-parameter meaning, so the 3 baseline for high schema coverage applies.

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 opens with a specific verb and object: 'Ask for one of the five guest seats at a Yerevan Product Coffee table,' which names the exact resource and distinguishes it from listing or note tools. It further orients by referencing list_upcoming_tables, making clear this tool consumes that listing and is not itself a listing tool.

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

Usage Guidelines5/5

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

It gives an explicit prerequisite: 'Call list_upcoming_tables first and pass one of its exact startsAt values,' and a mandatory two-call pattern with confirm:true. It also defines when the tool is not appropriate by stating 'A request is not a booking' and noting no seat is held for 3–5 days.

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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