On-chain activity intelligence — whale movements, large transfers, DEX volume anomalies, smart money tracking. $0.05 USDC. Payment is consumed on execution, including timeouts.
| Name | Required | Description | Default |
|---|---|---|---|
| chain | No | Chain filter (solana, base, ethereum) | |
| symbol | No | Token symbol (e.g., SOL, ETH, BTC) | |
| address | No | Token contract address | |
| timeframe | No | Lookback window (1h, 4h, 24h, 7d). Default: 24h |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses cost ($0.05 USDC) and that payment is consumed on execution including timeouts, which is useful. However, it does not state whether the operation is read-only, mutates state, or has rate limits.
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 very concise with only two sentences, no filler, and front-loads the core purpose. Every sentence adds value.
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 (4 parameters, no output schema), the description covers the purpose and some behavioral info (cost) but lacks details about return format, pagination, or whether results are alerts or data points. It feels adequate but could be more 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?
Schema coverage is 100% so baseline is 3. The description adds no extra meaning beyond the schema parameter descriptions; it does not explain relationships between parameters, provide examples, or clarify usage patterns.
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 states it provides 'on-chain activity intelligence' listing specific use cases like whale movements and large transfers. It clearly identifies the resource (on-chain data) but lacks a verb (e.g., 'retrieve') and does not distinguish from sibling tools like alpha_trending or alpha_stats.
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 instructions on when to use this tool versus alternatives. The description does not mention exclusions, prerequisites, or compare with any of the 18 sibling tools, leaving the agent without guidance for tool selection.
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.