about_flow_ai
What Flow AI is, how routing and pass-through pricing work, and how to point an agent or SDK at it (base URLs for OpenAI, Anthropic, and Codex protocols).
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
agent-bus
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
- First observed
TDQS
B3.1/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose whether the tool has side effects, read-only behavior, or any system impact. While it appears informational, the lack of explicit transparency leaves ambiguity.
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 a single, concise sentence that packs essential information without redundancy. It is well-structured and to the point.
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?
Given the tool's simplicity (no parameters or output schema), the description fully conveys what the tool offers. It covers the key topics—definition, routing, pricing, and configuration—so the agent has sufficient context to use it.
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 schema has zero parameters, and the description does not add parameter-specific meaning, but none is needed. Per the rubric, 0 parameters establishes a baseline of 4, which is appropriate here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description indicates the tool provides information about Flow AI, routing, pricing, and configuration URLs, but it lacks a clear action verb (e.g., 'Get' or 'Explain'). It is distinguishable from sibling tools, which are action-oriented, but its purpose is not as explicitly stated.
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 does not specify when to use this tool versus alternatives. There is no mention of conditions, prerequisites, or scenarios where this information would be needed, leaving the agent to infer appropriate usage.
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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TDQS
A3.8/5.0
Disambiguation5/5
Each tool has a clearly distinct purpose: the bus_* tools cover specific messaging operations (send, receive, reply, ack, check, inspect, signup, directory) with no overlap, and the Flow AI tools cover distinct queries/actions (about, prices, free models, search, delegate, convene). No two tools could be confused.
Naming Consistency3/5
The bus_* tools follow a consistent bus_<verb> pattern, but the Flow AI tools use varied conventions (about_flow_ai, get_live_prices, list_free_models, delegate_task) that don't share a prefix or consistent verb-noun structure. This mix is readable but not uniform across the whole set.
Tool Count5/5
14 tools is well within the ideal 3-15 range and each earns its place, covering two coherent sub-domains (agent bus messaging and Flow AI model services) without redundancy or bloat.
Completeness4/5
The bus messaging surface is complete: send, receive (lease), reply, ack, check status, list agents, inspect own mailbox, and signup. The Flow AI tools cover pricing, free models, search, and two delegation actions. Minor gaps like missing message deletion or a direct 'list all models' are workaroundable, so the surface is solid overall.