Flowlines - MCP Analytics

Get cohort details

get_cohort

Read-onlyIdempotent

Get one Flowlines cohort and its rules and metrics.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "reason": "<reason>",
      "user_intent": "<user_intent>",
      "namespace_id": "<namespace_id>",
      "cohort_id": "<cohort_id>"
    },
    "name": "get_cohort"
  }
}

Input Schema

Name	Required	Description
`reason`	Yes	A short phrase saying why you are calling this tool, for example: find unpaid invoices.
`cohort_id`	Yes
`user_intent`	Yes	One sentence describing what the user is trying to accomplish. Keep it the same across calls until the user's goal changes.
`namespace_id`	Yes	Flowlines namespace UUID.

Output Schema

Name	Required	Description	Default
`data`	Yes
`notice`	No
`truncation`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 19, 2026

TDQS

B3.3/5.0

Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and closed-world behavior, so the safety profile is covered. The description adds that rules and metrics are returned, but since an output schema exists this is redundant; it does not disclose permissions, error behavior, or other traits. With annotations doing the heavy lifting, a 3 is appropriate.

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?

One sentence, front-loaded with the verb and resource, with zero wasted words. It is as concise as a useful description can be.

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 simple read-only tool with an output schema and strong annotations, the description is minimally sufficient for selection. However, it lacks any usage context that would help the agent choose among sibling tools, leaving a clear gap.

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 75% (three of four parameters documented), and cohort_id is self-explanatory via its UUID format/pattern. The description adds no parameter guidance, so the schema carries the meaning. Baseline 3 is correct when structured fields do most of 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 specific verb 'Get', resource 'cohort', and scope 'one', and names the returned content ('rules and metrics'). The word 'one' implicitly distinguishes it from list_cohorts, though no sibling is named explicitly.

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?

The description gives no when-to-use guidance, no prerequisites, and no alternatives. It does not tell the agent when to pick this over list_cohorts, compare_cohorts, or other cohort-related siblings.

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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