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thenavidm
by thenavidm

List Teams

list_teams
Read-onlyIdempotent

Retrieve Calendly teams to manage organizational memberships and permissions; filter by user and paginate results for complete team oversight.

Instructions

List Teams. Reads Calendly data. Supports bounded opaque page_token retrieval. Required scopes: organizations:read.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
userNoFilter results to Teams associated with a specific user
countNoThe number of rows to return
accountNoNamed private Calendly account; selects credentials, not an organization URI.
all_pagesNoRead bounded opaque page_token pages; each request consumes quota. Not a snapshot or guaranteed complete backup.
max_itemsNoMaximum returned records with all_pages=true, default 1000. At most 100 requests; output includes continuation state.
page_tokenNoThe token to pass to get the next or previous portion of the collection

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true, so safety is covered. The description adds the required scope (organizations:read) and notes pagination is opaque/bounded, which is useful auth and retrieval context. It does not disclose quota-per-request behavior or that all_pages is not a complete snapshot, though the schema does.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short, front-loaded fragments: purpose, data domain, retrieval behavior, scopes. No wasted words, though the terse fragment style leaves little connective context for why each clause matters.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

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

For a read-only list tool with full schema coverage and rich annotations, the description is adequate: it names the resource, the data source, the pagination model, and the required scope. It omits the relationship to sibling team/group tools and the filter semantics, which would help an agent choose correctly among list_teams, list_groups, and get_team. No output schema exists, so return shape is also unaddressed.

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 six parameters carry their own descriptions in the schema. The description adds only a general note that page_token retrieval is bounded, which the schema already conveys via max_items/all_pages. Baseline 3 is appropriate when the schema does the work.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a clear verb (List) and resource (Teams), and the scope 'Reads Calendly data' tells the agent this is a Calendly-team collection. It does not name or differentiate itself from the sibling get_team/list_groups, but the resource is unambiguous.

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

Usage Guidelines3/5

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

The description hints at pagination via 'bounded opaque page_token retrieval' but never states when to use this tool versus get_team or list_groups, nor when to prefer account vs user filtering. Usage context is implied by the schema parameters rather than specified.

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