FactorWeave

list_futures

Read-onlyIdempotent

List the top-30 futures contracts that have per-ticker factor decomposition available. Returns ticker, the asset family (equity-index / energy / metals / rates / fx / crypto), and the latest snapshot (close, mom, rsi, oi_z20, oi_vol_ratio, comp_score). PRO tier or higher for the snapshot block; ticker list itself is FREE. Use the returned tickers with get_features to pull the full factor row (e.g. get_features(ticker="VX") for the VIX futures continuous contract).

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description
`count`	Yes
`tickers`	Yes
`snapshot_locked`	No	true for non-PRO tiers — snapshot fields are absent.

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive traits. The description adds valuable context about tier-based data availability (PRO for snapshot, free for tickers) and the exact output fields. This goes beyond the annotations without contradicting them, though it could mention sorting or pagination behavior.

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 two sentences: the first states the core functionality and output, the second provides usage guidance and an example. Every sentence earns its place, and the purpose is front-loaded in the first sentence. No 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 zero-parameter tool with an output schema and annotations, the description is exceptionally complete. It covers purpose, output fields, access tiers, and downstream usage with get_features. The example with VX clarifies the intent. There are no significant gaps given the tool's simplicity.

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, so the description correctly provides no parameter details. The schema is empty and needs no additional explanation. The baseline for 0 params is 4, and the description appropriately avoids superfluous parameter information.

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 the top-30 futures contracts with per-ticker factor decomposition, specifies the returned fields (ticker, asset family, snapshot), and distinguishes from siblings by explicitly linking to get_features. The verb 'List' and resource 'futures contracts' are specific and unambiguous.

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 gives explicit usage guidance by telling users to use the returned tickers with get_features, including a concrete example. It also notes the PRO tier requirement for the snapshot, implying when a user might only need the free ticker list. While it doesn't mention every alternative sibling, the guidance is clear and actionable.

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

Disambiguation4/5

Most tools target distinct resources (features, embeddings, labels, market context, risk clusters), but minor overlap exists: get_market_context includes a regime reading that get_market_regime also provides, and get_report_card bundles features that get_features offers separately. Descriptions are clear enough to resolve these overlaps.

Naming Consistency4/5

The predominant pattern is get_<noun> (get_features, get_labels, get_manifest, etc.), with two exceptions: find_similar (find_) and list_futures (list_). This is a small deviation but still follows a predictable verb-noun structure for retrieval, search, and enumeration actions.

Tool Count5/5

14 tools is well within the ideal range for a quantitative data server. Each tool serves a distinct purpose, from basic data retrieval (features, labels) to advanced analytics (similarity, risk clusters) and user management (alerts, usage). No tool feels redundant or missing.

Completeness4/5

The toolset covers the core data access and analytics needs for factor-based market analysis: retrieval, search, market context, and backtesting labels. Minor gaps include no generic ticker search or list (beyond futures), and no direct way to browse available factors beyond documentation, but these can be worked around via get_top and get_manifest.

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