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Flowlines - MCP Analytics

List cohorts

list_cohorts
Read-onlyIdempotent

List cohorts in one Flowlines namespace using API filters and cursor pagination.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoPage size. Defaults to 20.
cursorNoOpaque cursor from a previous page.
reasonYesA short phrase saying why you are calling this tool, for example: find unpaid invoices.
user_intentYesOne sentence describing what the user is trying to accomplish. Keep it the same across calls until the user's goal changes.
aggregate_idNo
namespace_idYesFlowlines namespace UUID.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
noticeNo
truncationYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is fully covered. The description adds the cursor-pagination behavior and namespace scoping, which is real value, but says nothing about auth requirements, rate limits, or result ordering. Baseline 3 given annotation coverage.

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?

A single efficient sentence with the resource and scope front-loaded and zero filler. It is appropriately sized for what it attempts, though the brevity comes partly from omitting usage guidance rather than from tight editing.

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?

With an output schema present the description needn't explain return values, and annotations cover safety. However, for a 6-parameter list tool the description omits any mention of the aggregate_id filter and the required reason/user_intent bookkeeping params, leaving the caller to discover filtering scope entirely from 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 coverage is 83%, so the schema already documents limit, cursor, reason, user_intent and namespace_id. The description's 'API filters' is vague and does not clarify the undocumented aggregate_id filter or add format detail beyond the schema. Baseline 3 applies.

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 specific verb+resource+scope: 'List cohorts in one Flowlines namespace.' An agent can distinguish it from get_cohort and compare_cohorts by the list-vs-single-vs-compare verb, though the description never explicitly names those siblings.

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

Usage Guidelines2/5

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

No when-to-use guidance, no prerequisites, and no routing to alternatives like get_cohort for a single cohort or compare_cohorts. 'Using API filters and cursor pagination' describes mechanics, not the conditions that should select this tool.

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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