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Flowlines - MCP Analytics

List MCP server actions

list_actions
Idempotent

List what Flowlines suggests doing next for the MCP servers in a namespace, in rank order. Each action says why, how it gets done (execution.mode and steps) and which criteria Flowlines checks. Each read runs Flowlines' checks first, so statuses are current; only a check completes an action, except a manual one (verification.manual), which a person marks done in the Flowlines app. Start with planned actions: the team chose them. Completed, dismissed and expired actions need no work. get_action reads one action, prepare_action takes it on before you work on it, and verify_action checks it when you finish.

Input Schema

NameRequiredDescriptionDefault
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.
namespace_idYesFlowlines namespace UUID.

Output Schema

NameRequiredDescriptionDefault
dataYes
noticeNo
truncationYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.3/5.0
Behavior4/5

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

Adds real behavior beyond the annotations: reads execute Flowlines' checks first, which explains why readOnlyHint is false despite a 'list' verb, and it discloses that only a check completes an action unless verification.manual requires a human in the app. It stops short of describing what the checks mutate or how many actions come back, leaving some side-effect detail implicit.

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?

Front-loads the core purpose, then groups semantics, lifecycle rules and sibling routing into three efficient sentences with no filler. Dense field references like execution.mode and verification.manual are compact but assume familiarity with the domain model.

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 annotations and an output schema present, the description covers what the return items contain and how to progress an action, which is the important remaining surface. It says nothing about result volume, ordering ties or paging limits for the ranked list, a minor but real gap for a list tool.

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 reason, user_intent and namespace_id are already documented in the schema. The description contributes nothing further about parameter meaning or format, which is the expected baseline when the schema does the heavy lifting.

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 concrete verb and resource ('List what Flowlines suggests doing next for the MCP servers in a namespace') and adds scope details: rank order, per-action rationale, execution mode and criteria. An agent can distinguish it from get_action, prepare_action and list_mcp_recommendations without opening any 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?

Explicitly says to start with planned actions, declares completed/dismissed/expired actions as needing no work, and routes to the three sibling tools by lifecycle stage (get_action reads one, prepare_action takes it on, verify_action checks it when done). When-to-use and which-alternative are both spelled out.

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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