Token safety assessment — audit status, rug pull signals, liquidity depth, holder concentration, honeypot detection, plus X and Reddit scam-report corroboration. $0.062 USDC. Payment is consumed on execution, including timeouts.
| Name | Required | Description | Default |
|---|---|---|---|
| chain | No | Chain for lookup (auto-detect if omitted) | |
| symbol | No | Token symbol (e.g., WIF) | |
| address | No | Token contract address (preferred for accuracy) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses payment cost ($0.062 USDC) and that payment is consumed even on timeouts, which is important behavioral context. However, it does not mention what happens if required parameters are missing (auto-detect fails?), rate limits, or other failure modes.
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 two sentences with no wasted words. The first sentence front-loads the purpose and key features, the second adds essential cost and execution behavior. Every sentence earns its place.
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 no output schema, the description should clarify what the tool returns (format, structure) but does not. It covers purpose, features, and cost but omits return value details and error handling. Adequate but with clear gaps.
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?
Input schema coverage is 100%, with each parameter described (chain, symbol, address). The description adds no further meaning to these parameters beyond what the schema provides, so a 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?
The description clearly states the tool's purpose: token safety assessment. It lists specific aspects like audit status, rug pull signals, liquidity depth, holder concentration, honeypot detection, and social corroboration, providing a precise verb-resource pair ('assess token safety'). This distinguishes it from sibling tools focused on other areas (e.g., alpha_news, alpha_sentiment).
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 implicitly indicates use for token risk evaluation but provides no explicit guidance on when to choose this tool over siblings (e.g., alpha_deep for deeper analysis, alpha_token for general info). It does not specify prerequisites or when not to use it.
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.