Finance Signal Bundle - get live computed signal: Gamma exposure for SPY/QQQ/IWM options chains: net GEX, gamma flip level, call/put gamma walls, and put/call open interest ratio. Positive g 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 burden. It discloses that the signal is 'live computed' and mentions a price of 0.05 via x402 (USDC on Base), indicating a cost/access mechanism. However, the 'Positive g Price' phrasing is ambiguous, and it does not clarify whether the optional wallet parameter relates to payment or free-tier limits, leaving important behavioral traits unclear.
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 short (two sentences) and front-loaded with the main purpose, but the 'Finance Signal Bundle' intro is vague and the second sentence has a confusing, possibly garbled phrase ('Positive g Price') that reduces clarity. It is not as clean or efficient as it could be.
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, the description lists metrics but does not explain the response format or structure. The payment and wallet interactions are unclear, and there is no guidance on how this signal differs from siblings. The tool appears simple (one optional param), but the output is likely complex, and the description leaves gaps in understanding the full context.
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?
Schema coverage is 100% for the single 'wallet' parameter, with a detailed description of the free-tier credits. The tool description adds no parameter information beyond that, so the baseline score of 3 applies; the description does not need to compensate.
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?
Description clearly states the tool provides a live computed signal for gamma exposure on SPY/QQQ/IWM options chains, listing specific outputs like net GEX, gamma flip level, call/put gamma walls, and put/call OI ratio. This distinguishes it from sibling signal tools by underlying assets and metrics. However, the phrase 'Positive g Price 0.05 via x402 (USDC on Base)' is confusing and detracts from 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 explicit when-to-use guidance or alternatives are provided. The purpose is implied by the content (options gamma signal), but with many sibling signal tools, the description does not explain when to choose this over others like processed_put_call or signal_market_stress. It merely describes the tool's contents without usage context.
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.