Deep multi-source research (Exa + Firecrawl + Claude + up to 99 tweets). $0.10 USDC. May take up to 60s. Payment is consumed on execution, including timeouts.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Research query (e.g., "Solana DeFi trends", "Base L2 ecosystem", token name) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries the full burden. It discloses multi-source usage, cost, timeout, and that payment is consumed on execution including timeouts. Could mention output format or error handling but is sufficiently transparent for a single-parameter tool.
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?
Single sentence with no wasted words. Key elements (multi-source, cost, timeout, payment consumption) are front-loaded and clearly communicated.
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?
Given the complexity (multi-source, cost, timeout, single param), the description covers the essential behavioral aspects. Missing details on output format or timeout behavior (e.g., what happens on timeout) but adequate for the tool's simplicity.
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 description coverage is 100% with example queries. The tool description does not add additional parameter information beyond the schema, so baseline score of 3 is appropriate.
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?
Clearly states it is a deep multi-source research tool listing specific sources (Exa, Firecrawl, Claude, tweets), cost, and timeout. Distinguishes from sibling tools like alpha_brief or alpha_search by emphasizing depth and multiple sources.
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?
Provides clear context: it is for deep research, costs $0.10 USDC, and may take up to 60s. Does not explicitly state when not to use it or name alternatives among siblings, but the depth/time/cost imply it is for thorough investigations.
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.
Each tool targets a distinct aspect of crypto alpha research (e.g., brief, calendar, compare, deep, macro, memecoin, narrative, news, onchain, perps_funding, portfolio, prediction, risk, search, sentiment, stats, subscribe, token, trending). Descriptions clearly differentiate purposes, minimizing ambiguity.
All tool names follow a uniform 'alpha_{descriptive_noun}' pattern with snake_case, making naming predictable and easy to navigate.
With 19 tools spanning a broad range of crypto intelligence (market data, sentiment, on-chain, risk, portfolio, news, etc.), the count is well-scoped for the server's purpose—neither too few nor excessive.
The tool set covers most key areas of crypto research (price, sentiment, on-chain, risk, news, calendar, narratives, portfolio, predictions, subscriptions). Minor gaps like a dedicated volume/anomaly tool are absent, but the set is largely comprehensive.