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Flowlines - MCP Analytics

Get an MCP server action

get_action
Idempotent

Get one Flowlines action: why Flowlines suggests it, its evidence, how it gets done (execution.mode, prerequisites and steps) and each criterion Flowlines checks. Runs the checks first, so the status is current. Action IDs come from list_actions or from a prompt copied from the Flowlines app.

Input Schema

NameRequiredDescriptionDefault
reasonYesA short phrase saying why you are calling this tool, for example: find unpaid invoices.
action_idYesAction ID from list_actions, or from a prompt copied from the Flowlines app.
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

A3.8/5.0
Behavior4/5

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

Annotations declare readOnlyHint=false, destructiveHint=false, and idempotentHint=true, but do not explain why a "get" is not read-only; the description resolves that by stating "Runs the checks first, so the status is current," disclosing the re-evaluation side effect and why results are fresh. It stops short of noting any cost, latency, or rate implications of running those checks, so it is strong but not exhaustive.

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?

Three compact sentences, each doing distinct work: contents, freshness behavior, and ID provenance. The payload enumeration is front-loaded in the first sentence with no filler or repetition.

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 detail return shapes, and it still adds the behavioral fact that checks are executed on read. For a fully-specified four-param read-with-side-effect tool this is nearly complete; only error or failure behavior is left implicit.

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 the schema already documents all four required parameters, including the provenance of action_id. The description restates that provenance but adds nothing about reason, user_intent, or namespace_id, so 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?

"Get one Flowlines action" gives a specific verb and resource and then enumerates what comes back (rationale, evidence, execution.mode, prerequisites, steps, criterion results), so an agent knows exactly what this returns. It does not contrast itself with adjacent siblings such as prepare_action, verify_action, or get_mcp_recommendation, which keeps it short of a 5.

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 tells the agent how to obtain valid input ("Action IDs come from list_actions or from a prompt copied from the Flowlines app"), which is useful routing guidance toward list_actions. It never states when to prefer prepare_action or verify_action instead, nor any exclusion or prerequisite, so usage is implied rather than prescribed.

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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