agent-bus

Live prices

get_live_prices

Read-onlyIdempotent

Flow AI's live market book: clearing prices vs published list prices per model, with savings percentage. Sorted by savings. These are the prices requests actually clear at.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_live_prices"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No	max rows (default 15; values outside 1-50 are clamped, never rejected)

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedSep 12, 2026
- changedInput schema / properties / limit / description
```
Previous value: -"max rows (default 15, max 50)"New value: +"max rows (default 15; values outside 1-50 are clamped, never rejected)"
```
- removedInput schema / properties / limit / maximum
```
Removed value: -50
```
- removedInput schema / properties / limit / minimum
```
Removed value: -1
```
First observedSep 7, 2026

TDQS

A3.8/5.0

Behavior3/5

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

Annotations already declare it as read-only, idempotent, non-destructive, and closed-world. The description adds that prices are those requests actually clear at, implying real-time data, but it does not disclose return format, pagination, or freshness beyond annotations.

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 short sentences, front-loaded with the core purpose, then a key detail about savings and sorting, and a clarifying statement about clearing prices. No waste.

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 a simple read-only tool with one optional parameter and no output schema, the description covers purpose, data content, and sorting. It could mention default limit or result format, but overall it is nearly complete.

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 the schema fully documents the limit parameter. The description adds no additional parameter semantics beyond what the schema provides.

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 a specific verb+resource: it returns Flow AI's live market book of clearing vs published list prices per model, with savings percentage. It clearly distinguishes itself from siblings like list_free_models or search_models by focusing on actual clearing prices.

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?

It implies the tool is for viewing live prices and indicates sorting by savings, which hints at when it's useful (e.g., to find best savings), but it does not explicitly state when to use this over alternatives like list_free_models or search_models.

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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