Skip to main content
Glama

flox_venue_guide

Learn how to build a market using the FLOX venue module: simulate multi-agent strategies on a shared order book, model market impact, and run matching engines, clearing, margin, and market-data feeds.

Instructions

Use when the user wants to BUILD A MARKET rather than trade on one: simulate several agents/strategies against one shared order book, model market impact with reacting counterparties, or run a matching engine, clearing ledger, margin/liquidation, market-data feed or venue gateway. Returns a Markdown guide to the optional FLOX venue module (flox::venue): headers, order vocabulary, derivatives waterfall, the multi-agent demo, build flag, and verification posture. No arguments. Cheap; pure bundled text. NOT for an ordinary single-strategy backtest over historical data -- use run_backtest.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. Addedv0.6.9

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does well. It discloses that the tool takes no arguments, is 'Cheap; pure bundled text,' and returns a specific Markdown guide listing contents. This gives a clear behavioral profile without hiding side effects or requiring inference.

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 front-loaded with the key use case, then provides a concise but informative breakdown of what the guide contains and the exclusion. Each sentence earns its place; no filler or repetition. It is appropriately sized for the complexity of a no-argument guide tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite lacking an output schema and annotations, the description is self-sufficient. It explains the guide's contents and the tool's context, and since it is a static informational resource, there are no side effects or return values left unexplained. The exclusion to run_backtest also gives the agent enough context to choose 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 tool has zero parameters, and the schema already reflects that with an empty properties object. The description adds 'No arguments,' which is redundant but harmless. According to the baseline for 0 params, a score of 4 is appropriate; there is nothing substantive to add.

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 explicitly states the tool's purpose: 'Returns a Markdown guide to the optional FLOX venue module' and opens with 'Use when the user wants to BUILD A MARKET rather than trade on one.' It clearly distinguishes this from trading tools and specifically names an alternative (run_backtest) for the excluded case, so it is unambiguous versus siblings.

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?

Usage guidance is explicit: it lists concrete scenario examples (simulate agents, model market impact, run matching engine) and gives a clear exclusion with a suggested alternative: 'NOT for an ordinary single-strategy backtest over historical data -- use run_backtest.' This meets the highest bar for when-to-use and when-not-to-use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/FLOX-Foundation/flox'

If you have feedback or need assistance with the MCP directory API, please join our Discord server