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Compound Interesting — market intelligence

Overnight positioning on US names (24/7 perps)

list_equity_perp
Read-only

Funding rate and open interest for the ~51 US single names listed on a 24/7 perpetual futures venue, ranked by notional. This is the ONLY source here that moves outside US market hours, so it is what to check overnight and at weekends. High positive funding means longs are paying to hold — crowded, squeeze-fragile. The mark price is a venue mark, NOT the stock price.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many names to return.

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description adds critical behavioral context: the mark price is a venue mark, not the stock price, and high positive funding indicates crowded, squeeze-fragile positioning. This is valuable non-obvious information that significantly enhances understanding.

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 dense, purposeful sentences. The first defines the tool, the second specifies when to use it, and the third explains how to interpret the data. Zero fluff or redundancy.

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?

For a simple tool with one parameter, high schema coverage, and a readOnly annotation, the description is remarkably complete. It covers purpose, usage timing, interpretation, and a critical caveat about the mark price. No output schema is needed to understand the returned data.

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 already describes the 'limit' parameter (100% coverage), so baseline is 3. The description adds meaning by revealing the universe size (~51 names) and that results are ranked by notional, which informs how limit should be interpreted and used.

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 clearly states the tool lists funding rate and open interest for ~51 US single-name perpetuals, ranked by notional. This specific verb+resource+scope distinguishes it from sibling tools like get_equity_perp, and the added 'ONLY source here that moves outside US market hours' context further differentiates its purpose.

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 explicitly states when to use it ('what to check overnight and at weekends') and even explains it is the 'ONLY source' for that use case. It does not explicitly name alternatives or state when not to use it, but the guidance is clear and practical.

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

A4.2/5.0
Disambiguation3/5

get_composite and get_consensus both return per-ticker consensus with dimension breakdowns, creating ambiguity; agents might call the wrong one. Other tools are clearly distinct, but this overlap requires extra care.

Naming Consistency5/5

All tools follow a verb_noun pattern: get_ for single entities, list_ for collections, and rank/search/screen as action verbs. The pattern is consistent and predictable across the entire set.

Tool Count5/5

15 tools is well-scoped for a market intelligence server, covering single-ticker queries, lists, discovery, and market-level signals without unnecessary bloat.

Completeness4/5

The surface covers core workflows: ticker resolution, consensus, evidence, trades, positioning, screening, and market signals. Minor gaps exist (e.g., historical consensus or direct ticker comparison), but they are not critical.

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