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processed_fear

Finance Signal Bundle - get live computed signal: Cross-asset fear gauge (0-100) synthesized from VIX, gold/equity/crypto volatility, valid intraday. Price 0.01 via x402 (USDC on Base).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
walletNooptional 0x wallet for X-Wallet free tier (free credits every month: 100 anonymous or 5000 with a bound wallet)

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description must disclose behaviors. It mentions pricing (0.01 via x402 on Base) and intraday validity, which are useful. However, it omits details such as whether wallet binding affects output, what response format is returned, and any rate limits or authentication requirements.

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 a single sentence that packs the signal type, source, scale, validity, and pricing. Every word contributes meaning, and it is front-loaded with the core purpose.

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

Completeness3/5

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

For a paid tool with no output schema or annotations, the description covers the core signal and pricing but lacks details on the x402 payment flow, the free tier wallet behavior, and expected return shape. These gaps could hinder an agent's invocation.

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?

The single optional 'wallet' parameter is fully described in the schema (100% coverage), so the baseline is met. The description does not mention this parameter, but the schema already explains its purpose and free tier implications.

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 provides a live cross-asset fear gauge (0-100) synthesized from VIX, gold/equity/crypto volatility, valid intraday. This specific verb+resource (get signal) and detailed scope distinguish it from generic sibling tools.

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

Usage Guidelines2/5

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

The description gives no guidance on when to use this tool versus alternatives like processed_vix_stress or signal_market_stress. It only describes the product's nature without specifying selection criteria or exclusions.

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

C2.6/5.0
Disambiguation2/5

Nearly all 80+ processed_/signal_ tools share the same boilerplate description and overlapping coverage areas (e.g., processed_global_markets vs. processed_global_indices vs. signal_global_indices; processed_crypto_funding_rate vs. processed_crypto_funding_rates), so an agent cannot reliably distinguish them. The generic ai_gateway, fetch_data, and list_products also have somewhat fuzzy boundaries around data access. Only broad asset categories in the names provide any separation.

Naming Consistency3/5

Core tools use verb-first imperative names (fetch_data, get_product_info, list_products), while the vast majority use adjective/noun prefixes (processed_*, signal_*), so the set mixes conventions. Within each cluster naming is consistent and all names are readable snake_case, but the 87-tool surface has no single predictable verb_noun pattern. Minor singular/plural inconsistencies like processed_crypto_funding_rate vs. processed_crypto_funding_rates add friction.

Tool Count1/5

87 tools is an extremely large surface for an MCP server, and most are variant data products that could be one fetch_data call with a product identifier. This falls into the >50 extreme range. The generic list/get/fetch primitives make the 80+ product-specific endpoints especially redundant.

Completeness4/5

The core consumer flow is covered: list products, inspect product info, and fetch a product (with payment challenge handling). Missing wallet/credit/balance tools and search/filtering are notable but work-aroundable. For a read-only data marketplace the lifecycle is largely complete.

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