Finance Signal Bundle - get live computed signal: Processed analytics layer over geopolitical risk: 30-period percentile rank, 4-period momentum, and a plain-language trend verdict. Turns ra 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?
With no annotations, the description carries the behavioral burden and does provide meaningful detail: it reveals the computed metrics, the plain-language verdict, and payment via 'Price 0.01 via x402 (USDC on Base)'. The 'Turns ra' fragment is garbled, and auth/rate-limit behavior is omitted, but the core signal and paid nature are disclosed.
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 description front-loads the signal purpose and metrics in a fairly compact format, but the sentence 'Turns ra Price 0.01 via x402 (USDC on Base)' is malformed and undermines clarity. The colon-heavy structure is serviceable but not polished.
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 description names the expected analytical outputs and payment channel, which is useful given there is no output schema. However, it leaves gaps around response shape, time period, how x402 payment is triggered, and how this relates to sibling geo/risk tools, so the agent may need to infer operational details.
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 sole parameter, wallet, is fully documented in the input schema, including free-tier credit details, so schema coverage is effectively 100%. The description adds no additional parameter-level guidance, warranting the baseline score of 3.
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 clearly states that the tool retrieves a live computed signal and is a processed analytics layer over geopolitical risk, listing specific outputs (30-period percentile rank, 4-period momentum, trend verdict). It is specific enough about the resource and operation, though it does not explicitly contrast with siblings like signal_geo_risk or processed_worldtension.
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?
'Processed analytics layer' and 'live computed signal' imply this is the enriched geopolitical-risk signal tool, but the description never states when to choose it over alternatives such as signal_geo_risk or processed_worldtension. The usage context is only implied, not explicitly guided.
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.