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Whenly — group meeting scheduler for AI agents

create_event

Create a free group-scheduling event (like When2meet/Doodle) and get a shareable link. Use this when a human asks you to find a time for a group to meet. Returns a public event_url anyone can open (no login) to mark when they're free, plus an admin note. Then poll get_results to see the best time.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tzNoTimezone label shown to participants, e.g. "US/Eastern" (default "local").
datesYesCandidate dates to consider, each as YYYY-MM-DD. 1–31 dates.
titleYesWhat the meeting is for, e.g. "Team sync" or "Dinner with friends".
end_hourNoLatest hour to consider, 1–24 (default 17 = 5 PM).
start_hourNoEarliest hour to consider, 0–23 (default 9 = 9 AM).
slot_minutesNoTime-slot granularity: 30 or 60 (default 60).

Schema Changelog

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

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are provided, so the description carries the behavioral disclosure burden. It discloses that the event is public, that anyone can open the returned event_url without login, and that an admin note plus the event URL are returned. It doesn't cover lifecycle, permissions, or rate limits, but the key behavioral traits are meaningfully surfaced.

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?

Three dense sentences cover purpose, usage trigger, return values, and the follow-up action. There is no fluff or repetition of schema details, and the most decision-relevant information is front-loaded.

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?

With no output schema, the description reasonably compensates by naming the event_url, the admin note, and the get_results polling step. The main gap is that the 'admin note' is left vague and lifecycle details are absent, but the agent has enough to invoke the tool and continue the workflow correctly.

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 the input schema already documents all six parameters. The tool description adds no per-parameter semantics beyond what the schema provides, so it meets the baseline but doesn't go above it.

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 resource ('Create a free group-scheduling event'), adds a helpful analogy (When2meet/Doodle), and names the concrete deliverable (a shareable link). It clearly distinguishes the create action from the sibling get_results by framing get_results as the follow-up poll step.

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?

It explicitly states when to use the tool: 'Use this when a human asks you to find a time for a group to meet.' It also tells the agent the next step ('Then poll get_results to see the best time'), which clarifies workflow. It lacks an explicit when-not-to-use condition, so it doesn't fully earn 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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TDQS

A4.2/5.0
Disambiguation5/5

The two tools have completely distinct purposes: create_event sets up a new scheduling poll, while get_results reads responses from an existing poll. There is no ambiguity or overlap between them.

Naming Consistency5/5

Both tool names follow the same verb_noun snake_case pattern: create_event and get_results. This is consistent and predictable.

Tool Count3/5

Two tools feels thin for a server, though the narrow workflow of creating an event and then polling for results is cohesive. Each tool earns its place, but the surface is minimal.

Completeness4/5

The create-and-poll workflow is complete for the basic group scheduling use case, but there are no update or delete capabilities for events. Agents can work around mistakes by creating new events, so the gap is minor.

Resources