Finance Signal Bundle - get live computed signal: Processed analytics layer over commodities: 30-period percentile rank, 4-period momentum, and a plain-language trend verdict. Turns raw seri Price 0.01 via x402 (USDC on Base).
| Name | Required | Description | Default |
|---|---|---|---|
| wallet | No | optional 0x wallet for X-Wallet free tier (free credits every month: 100 anonymous or 5000 with a bound wallet) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the behavioral disclosure burden. It does disclose that the signal is live/computed, lists the analytics transformations, and mentions a cost of '0.01 via x402 (USDC on Base)', which is useful context. However, it omits update frequency, data source, and the meaning of the incomplete 'Turns raw seri Price 0.01' clause.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The core signal description is reasonably compact and front-loaded, but the final sentence is malformed/truncated ('Turns raw seri Price 0.01 via x402'). The opening also repeats 'Bundle', 'live computed signal', and 'Processed analytics layer' in close succession, adding minor redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The absence of an output schema raises the bar, and the description partially compensates by naming three return components and a pricing detail. Still, it never clarifies how the plural 'processed_commodities' differs from the singular 'processed_commodity', what commodity universe is covered, or the structure of the returned signal bundle.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter, wallet, is fully described in the input schema with 100% coverage, including the free-tier credit distinction. The description itself adds no parameter-level meaning, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a concrete resource (commodities), an action ('get live computed signal'), and the computed outputs ('30-period percentile rank, 4-period momentum, and a plain-language trend verdict'), so it is not a tautology. However, it does not differentiate from the sibling 'processed_commodity', and the final sentence 'Turns raw seri Price 0.01 via x402' is garbled, which slightly muddies the clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to prefer this tool over alternatives. With siblings like processed_commodity, signal_gold, and signal_energy present, the description offers no selection criteria or exclusions, only an implied 'use this for live computed commodity signals'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.