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flow_status

Assess OmniFlow bridge and extension state to confirm a live Flow tab and valid license, preventing queued tasks from stalling.

Instructions

Bridge and extension state: whether the OmniFlow extension is connected, whether a Google Flow project tab is open, what is queued — plus extension.director, the director playbook. Call it BEFORE generating: without a live Flow tab tasks just pile up. If license is "expired" the extension has no access: ask the user to activate a key at lingoflow.pro/omniflow; the queue resumes by itself after activation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.1.2

TDQS

A4.6/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses what state is inspected and reveals important behavior such as queue auto-resuming after license activation. It stops short of stating whether the call is side-effect-free or describing the exact response format, so it is not a 5.

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?

The description is compact and front-loaded: it opens with the returned state categories, then immediately gives actionable sequencing and license guidance. Every sentence contributes useful information with no repetition or padding.

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 no output schema and no annotations, the description does well to enumerate the key state fields and preconditions. It could be more explicit about possible values or response shape, but the tool is simple and the guidance is sufficient for an agent to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has zero parameters, so there is nothing for the description to clarify. Per the baseline for parameterless tools, this is fully adequate.

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?

The description states exactly what the tool reports: connection state, open Flow tab, queued items, and the director playbook. This is clearly a status/read tool and is easily distinguished from sibling action tools like flow_generate, flow_edit, flow_wait, and flow_cancel.

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?

It gives an explicit directive to call the tool BEFORE generating, with a concrete consequence: without a live Flow tab, tasks pile up. It also provides conditional handling for an expired license, including the next user action and expected queue behavior after activation.

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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