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submit_availability

Mark your availability on a when2meet poll by submitting your name and selected time slots, allowing organizers to view your schedule.

Instructions

Sign in and mark availability on a when2meet poll.

Args: url: when2meet poll URL name: Your name as it should appear on the poll slot_indices: Zero-based slot indices to mark available password: Per-event password for returning participants timezone: IANA timezone used when loading the poll dry_run: Preview only (default true for safety) on_name_conflict: error | alternate_suffix — when password fails for existing name agent_name: Model label for alternate name, e.g. Claude (default: WHEN2MEET_AGENT_NAME env)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
nameYes
dry_runNo
passwordNo
timezoneNoAmerica/New_York
agent_nameNo
slot_indicesYes
on_name_conflictNoerror

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Install Server

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden. It discloses the safe default with 'dry_run: Preview only (default true for safety)', explains name-conflict behavior, and notes password and timezone handling. It could be more explicit about permanent effects when dry_run is false, but the safety default and conflict behavior are valuable disclosures.

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 is tightly structured as a one-line purpose followed by a compact argument list. Each parameter gets a single useful line, and no filler or redundant prose softens the value. The safety rationale for dry_run is the only extra detail and it earns its place.

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 an 8-parameter tool with no annotations and zero schema coverage, this description is remarkably complete. It explains all parameters, relevant defaults, conflict handling, and safety behavior. The presence of an output schema means return values do not need to be described here.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description fully compensates. Every parameter is explained in useful terms: 'Zero-based slot indices', 'IANA timezone', 'when password fails for existing name', and the meaning of on_name_conflict values. This far exceeds the bare 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?

The description begins with a specific verb-resource pair: 'Sign in and mark availability on a when2meet poll.' This clearly distinguishes it from sibling tools like get_poll, preview_availability, and find_common_availability, which have different purposes. The additional argument documentation reinforces the operational scope.

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 opening sentence provides clear context: the tool is for marking availability, so an agent can infer when to use it. It does not explicitly name sibling alternatives or state when not to use it, but the purpose is unambiguous enough that the use case is recognizable.

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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