AI-filtered crypto news from CoinTelegraph, Decrypt, CoinDesk, Blockworks + X/Twitter with AI synthesis. $0.02 USDC. Payment is consumed on execution, including timeouts.
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | Search query for news filtering (e.g., "bitcoin ETF flows") | |
| token | No | Alias for query token symbol (e.g., "BTC", "ETH") | |
| category | No | Source category filter (coindesk, cointelegraph, decrypt, blockworks) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses a $0.02 USDC cost consumed on execution including timeouts, which is a critical behavioral trait. However, it does not mention other behaviors like rate limits or output format, but the cost and timeout transparency is valuable.
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?
Two sentences: first describes purpose and sources, second explains payment and timeout behavior. No fluff, but the first sentence is dense with source names. Efficient overall.
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 covers the main functionality and cost but lacks details about the output format or what 'AI synthesis' produces. Given no output schema, this is a gap. Adequate but not complete.
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 100% description coverage (query, token, category are described clearly). The description adds no extra meaning beyond what the schema already provides, so baseline 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?
The description clearly states it provides AI-filtered crypto news from specific sources like CoinTelegraph, Decrypt, CoinDesk, Blockworks, and X/Twitter. This distinguishes it from sibling tools like alpha_trending or alpha_sentiment, which focus on other aspects of crypto analysis.
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?
The description gives context (sources and cost) but does not explicitly state when to use this tool versus alternatives. No exclusions or when-not-to-use guidance are provided, though the source specificity implies its domain.
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.