new_tokensDiscover recently launched Solana tokens. Filters by liquidity and risk score, ranked safest first.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of tokens to return (1-20) | |
| max_risk_score | No | Maximum risk score (0-1) | |
| min_liquidity_usd | No | Minimum liquidity in USD |
Changes observed during successful MCP inspections.
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses key behaviors: filtering by liquidity and risk score, and ranking safest first. However, it does not describe return format, pagination, data freshness, or any limitations (e.g., source of tokens, time window for 'recently launched'). This is adequate for a simple read-only list tool but leaves some gaps.
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, concise sentence that front-loads the primary purpose ('Discover recently launched Solana tokens') and includes key details without fluff. Every word earns its place, making it highly scannable for an AI agent.
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 tool's simplicity (3 optional parameters, no output schema), the description covers the essential context: what the tool does, how results are filtered and ordered. It lacks mention of output shape or additional constraints, but for a straightforward listing tool, this is sufficiently complete. A more detailed description would be beneficial but is not necessary.
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 already fully documents all three parameters with descriptions (100% coverage). The description adds a link between the filters (liquidity and risk) and the parameters, and mentions the safety ranking, but does not provide additional parameter-level meaning beyond the schema. The baseline of 3 applies due to high schema coverage.
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 function: 'Discover recently launched Solana tokens.' It specifies the resource (Solana tokens) and the action (discover), and adds distinguishing details (recently launched, filters, ranking). While it doesn't explicitly name sibling tools, the unique scope and sorting criteria set it apart from generic feed tools like 'feed_latest'.
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 implies when to use the tool: when you want recently launched tokens filtered by liquidity and risk, ranked safely. However, it provides no explicit guidance on when not to use it or which sibling tools to prefer (e.g., 'feed_latest' for general feeds, 'trending_signals' for trends). The usage context is inferred rather than stated.
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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