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List B2match participants

list_participants
Read-onlyIdempotent

Retrieve public participants for a B2match event as compact summaries, with optional search, pagination, and detail mode for full records.

Instructions

List public participants as a compact summary. Set detail=true for the fuller record; use get_participant for one profile.

Input Schema

NameRequiredDescriptionDefault
afterNoOpaque pagination cursor from a previous response.
eventYesB2match event URL, slug/euid, or numeric event id.
firstNoPage size, capped at 50.
queryNoFree-text search on participant name, organisation, or profile text.
detailNotrue returns the full participant records instead of compact summaries (larger output).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.2.1
    • addedInput schema / properties / detail / description
      Added value: +"true returns the full participant records instead of compact summaries (larger output)."
    • addedInput schema / properties / query / description
      Added value: +"Free-text search on participant name, organisation, or profile text."
  2. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive/open-world, so the burden is light; the description adds genuinely new context by announcing the compact-versus-full output tradeoff and the 'public' scope of the results. It stops short of covering pagination or truncation behavior beyond the cursor defined in the schema.

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?

Two short sentences, zero filler, with the default behavior front-loaded before the two escalation paths. Every clause earns its place by changing how the agent would call the tool.

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 adequately signals the return shape (compact summaries vs full records) and the public-only scope. It could say more about page-size limits and cursor termination, but the required event parameter and filtering are fully covered by the schema.

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 all five parameters including detail and the cursor are already documented. The description restates the detail flag's effect but adds no format, default, or interaction detail beyond the schema and the -50 cap, so the baseline 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?

States a specific verb and resource (list public participants) plus the shape of the return (compact summary), and explicitly contrasts itself with get_participant so an agent can distinguish it from the single-profile sibling 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 explicit routing: normal use for a compact list, detail=true for the fuller record, and get_participant when only one profile is needed. The alternatives and the condition that selects them are named rather than left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.