Finance Signal Bundle - get live computed signal: Custom altcoin season index: percentage of top 50 coins (excl. stablecoins) outperforming BTC over 30 days. >=75 indicates altseason, <=25 i 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 provided, the description carries the full burden of disclosing behavioral traits. It does mention the cost (Price 0.05 via x402) and free tier (wallet), which is beyond schema info. However, it lacks details on the exact response format, data freshness, or any potential side effects. The truncated sentence ("<=25 i") also leaves part of the threshold behavior 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 reasonably sized but contains a truncated sentence ("<=25 i") and a somewhat run-on structure. It starts with a generic 'Finance Signal Bundle' prefix that could be trimmed. The information is not presented as efficiently as it could be, but it's not overly verbose.
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 tool is simple with one optional param and no output schema, so the description should explain what is returned. It indicates the value is a percentage and gives interpretation thresholds, which is helpful. However, it does not specify the exact return format (e.g., JSON structure, timestamp), nor does it fully complete the threshold explanation due to truncation. With no output schema, the description should provide more complete return info.
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 has one optional param 'wallet' with a complete description covering the free tier, so schema description coverage is 100%. The tool description adds no additional parameter semantics, which is acceptable given the schema already handles it, hence baseline 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 it provides a live computed altcoin season index, with specific details about the calculation (percentage of top 50 coins excluding stablecoins outperforming BTC over 30 days) and thresholds (>=75 indicates altseason). This clearly distinguishes it from the many sibling signal tools.
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?
It implies when to use (to get altcoin season data) but does not explicitly state when to use it over alternatives, nor does it mention any exclusions or alternative tools. Given the large number of sibling signals, explicit guidance would be beneficial, but the description's clarity about the metric provides some implicit 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.