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Flowlines - MCP Analytics

Get session details

get_session
Read-onlyIdempotent

Get one Flowlines session, including its analysis and turn tree. Results may contain end-user personal data: quote minimally and mask direct identifiers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
reasonYesA short phrase saying why you are calling this tool, for example: find unpaid invoices.
session_idYessessionId returned by list_sessions. Use the same namespace as that session.
user_intentYesOne sentence describing what the user is trying to accomplish. Keep it the same across calls until the user's goal changes.
namespace_idYesFlowlines namespace UUID.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
noticeNo
truncationYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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 covered. The description adds genuinely new behavioral context the annotations cannot: the response may contain end-user PII and the agent is instructed to quote minimally and mask direct identifiers. It still says nothing about size, pagination, or namespace/permission constraints on retrieval.

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 sentences, zero filler. The capability statement is front-loaded and the PII handling rule follows immediately; every clause earns its place.

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 an output schema present the description need not enumerate return fields, and the read-only annotations cover safety, so what remains is the privacy handling instruction, which is supplied. The only gap is operational context such as result size, pagination, or required access level for retrieving another namespace's session.

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 100%, so all four parameters (reason, user_intent, namespace_id, session_id) are fully documented in the schema, including the instruction to reuse the same namespace as the listed session. The description adds no parameter-level meaning beyond that; baseline 3 is appropriate.

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 and resource ('Get one Flowlines session') and names the payload contents ('its analysis and turn tree'), so the agent knows exactly what comes back. The singular 'one ... session' implicitly contrasts with list_sessions, but the sibling is never named, so differentiation requires a small inference.

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?

Usage is only implied: fetch a single session once you have its ID, following a list_sessions call. There is no explicit when-to-use/when-not guidance and no named alternatives (e.g. get_turn for drill-down, aggregate_sessions for roll-ups), which would matter given the many sibling read tools.

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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