FullClass

List underfilled events

list_underfilled_events

Read-onlyIdempotent

Upcoming events in the next days_ahead days (default 30) filled below threshold_percent (default 50), emptiest first. Use it to answer which classes need promoting. Events with no capacity limit are left out, and so are private buyouts, which are sold whole to one customer. For fill over a past period, use get_fill_rates. Returns at most 50 events per call; when has_more is true, raise offset for the next page.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_underfilled_events"
  }
}

Input Schema

Name	Required	Description
`limit`	No	maximum events to return; defaults to and is capped at 50
`offset`	No	how many events to skip, for paging
`days_ahead`	No	how many days ahead to look; defaults to 30
`threshold_percent`	No	report events filled below this percentage; defaults to 50

Output Schema

Name	Required	Description
`to`	Yes
`from`	Yes
`events`	Yes	emptiest first
`has_more`	Yes
`returned`	Yes
`timezone`	Yes
`total_found`	Yes	events under the threshold before limit and offset were applied
`events_checked`	Yes	scheduled events in the window that have a capacity set
`threshold_percent`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 5, 2026

TDQS

A4.7/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds genuinely new behavioral context: sort ordering, silently omitted event types, a hard 50-result cap, and the has_more/offset paging protocol. It does not mention authorization or rate limits, but none appear relevant for a read-only listing.

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 tight sentences: filter scope and ordering first, then the use case, then exclusions, then the alternative tool and pagination. No filler, 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.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need no explanation; the description instead covers the things structured fields cannot: sort order, silent exclusions, result cap, paging workflow, and the sibling tool to use instead. Nothing needed to select or invoke this correctly is missing.

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?

Schema description coverage is 100%, so all four parameters are already documented and the baseline is 3. The description reinforces the defaults inline (30 days, 50 percent) and, more usefully, explains the pagination contract linking has_more to raising offset, which the schema alone does not state.

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?

States a specific verb and resource (list upcoming events filtered by fill percentage), plus the sort order (emptiest first) and default windows. It is clearly distinguishable from list_upcoming_events (unfiltered) and get_fill_rates (past-period fill analysis) without opening either schema.

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?

Gives an explicit use case ('answer which classes need promoting') and names the alternative tool with the condition that selects it ('For fill over a past period, use get_fill_rates'). It also states two exclusion conditions (no capacity limit, private buyouts), so the agent knows what results will silently be absent.

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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