Finance Signal Bundle - get live computed signal: Composite risk score (0-100) from four factors: fear & greed index, perpetual funding rate (long leverage crowding), long/short account rati Price 0.05 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 full burden of behavioral disclosure. It mentions the signal is 'live computed' and includes a price, but it does not disclose output format, how the score is delivered, any rate limits, or whether a wallet is required. The description is incomplete and even contains a truncated word ('rati') that obscures behavior.
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 is a single sentence, but it is not well structured due to a typo ('rati Price' likely missing 'o') and an unnecessary 'Finance Signal Bundle' prefix. It is somewhat front-loaded with the action, but the flow is disrupted and would benefit from clearer punctuation or separate sentences.
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?
With no output schema and no annotations, the description should explain what the caller receives beyond the score range. It does not mention the output shape, how to interpret the composite score, or how the optional wallet affects access. The description appears cut off, leaving out important contextual information for a paid tool.
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 input schema provides 100% coverage for the only parameter (wallet), including its optional nature and free-tier advantages. The tool description adds no parameter-specific semantics; the price note is not tied to a parameter. Baseline 3 is appropriate since schema already explains the parameter.
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 the tool's function with a specific verb ('get') and resource ('live computed signal'), and specifies exactly what it computes: a composite risk score (0-100) from four named factors. This distinguishes it from sibling tools like processed_fear (single factor) and other processed_* signals.
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 provided on when to use this tool versus alternatives. It only describes what the signal is and mentions the price, but does not suggest scenarios, prerequisites, or exclusions. There is no comparison to other signal tools in the sibling list.
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.