token_intel
Lightweight token lookup: price, market cap, volume, and basic risk assessment for any EVM or Solana token.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| chain | No | Blockchain network | ethereum |
| address | Yes | Token contract address or name |
Lightweight token lookup: price, market cap, volume, and basic risk assessment for any EVM or Solana token.
| Name | Required | Description | Default |
|---|---|---|---|
| chain | No | Blockchain network | ethereum |
| address | Yes | Token contract address or name |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It implies a read-only operation ('lookup') but does not explicitly confirm safety, rate limits, or side effects. It claims 'any EVM or Solana token', yet the chain enum is limited to five chains (ethereum, base, solana, polygon, arbitrum), which is a scope mismatch that is not disclosed. The phrase 'basic risk assessment' leaves what that entails undefined, and there is no mention of output format or potential errors.
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 a single sentence that is concise and front-loaded with the core purpose. Every word earns its place; there is no filler or redundant phrasing.
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 large set of sibling tools, the description is incomplete for an agent to choose correctly. It does not explain what 'basic risk assessment' entails, which chains are actually supported (despite saying 'any EVM'), or what the return structure looks like. There is no output schema, so the description should clarify the response format, but it does not. An agent could easily confuse this with token_research or token_risk_metrics.
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 the baseline is 3. The description does not add any parameter-specific meaning beyond the schema; it lists output fields rather than clarifying the input parameters. The address description in the schema already mentions 'Token contract address or name', and the chain enum is self-explanatory. No extra semantics are provided.
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 a specific verb ('lookup') and resource ('token') and lists the fields returned (price, market cap, volume, basic risk assessment). It positions itself as 'lightweight', which hints at a lighter alternative to heavier tools, but it does not explicitly differentiate from siblings like token_research or token_compare. The purpose is clear but not sharply delimited.
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 no explicit guidance on when to use this tool versus the many token-related siblings (e.g., token_research, token_compare, token_risk_metrics). It implies a quick check through the word 'lightweight', but does not state conditions like 'use for a quick snapshot, use token_research for deep analysis'. No exclusions or alternatives are named.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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