dydx-agent-gateway

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Market Digest

market_digest

Read-onlyIdempotent

Retrieve a one-call market briefing: detector events, funding extremes, and verified leaderboard top for the essential daily overview.

Instructions

One-call market briefing: latest detector events + funding extremes (liquid markets only) + verified leaderboard top. The daily briefing an agent (or human) needs before anything else. Returns: events (up to 5, payload flattened into each row), funding (top-5 funding rows, markets with >= $100k OI) and leaderboard_top (top-3 by pnl_window: address, pnl_window, equity, day_winrate). Example: market_digest()

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": "market_digest"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.3.0Sep 5, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description is not burdened with basic safety disclosure. It adds meaningful behavioral details beyond annotations: result caps (up to 5 events, top-5 funding, top-3 leaderboard), filtering thresholds (>= $100k OI), and payload flattening. No contradiction with 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?

The description is compact and front-loaded: the first line summarizes the entire purpose, and the following lines detail return structure. Every sentence adds value; there is no fluff or restatement of the tool name. The example is short and useful.

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?

Given zero parameters, rich annotations, and an output schema, the description provides sufficient context for correct invocation. It explains what data is included, how much, and under what filters, which is complete for an agent to decide to call 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 tool has zero parameters and schema description coverage is 100%, so there is no parameter ambiguity. Per the baseline for zero-parameter tools, a 4 is appropriate. The included example call, 'market_digest()', reinforces the no-argument invocation.

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 and resource: it is a one-call market briefing combining latest detector events, funding extremes, and verified leaderboard top. It clearly differentiates itself from siblings like latest_events, funding_heatmap, and leaderboard by framing itself as an aggregate digest. The return components are explicitly enumerated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description says this is 'The daily briefing an agent (or human) needs before anything else,' which clearly implies it should be used for initial market orientation. It does not explicitly name alternatives or conditions for when not to use it, but the composite nature makes the intended use case reasonably clear.

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