sample_mint
Free: a full risk-card sample for one mint aged >= 300 s (delayed), to see the paid mint_risk_card shape.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Free: a full risk-card sample for one mint aged >= 300 s (delayed), to see the paid mint_risk_card shape.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses that the tool is free, delayed, and constrained to one mint aged >= 300 seconds. However, it does not explicitly state side effects, permissions, or whether any state changes occur, leaving some behavioral ambiguity.
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 efficient sentence, front-loading the key value proposition ('Free') and the core purpose. There is no redundant wording.
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?
For a zero-parameter sample tool, the description is sufficient: it explains what the output is for, the free nature, the delay, and the relationship to the paid sibling. No output schema or additional context is strictly 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 tool has zero parameters, so the baseline is 4. The description adds relevant contextual detail about the sample criteria (one mint, age threshold, delayed), even though it is not describing a parameter.
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 that this tool provides a free full risk-card sample for one mint and explicitly frames it as a way to preview the paid mint_risk_card shape. This distinguishes it from the sibling mint_risk_card tool.
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?
It gives clear context for when to use the tool: when you want to preview the paid mint_risk_card output without paying. It does not explicitly state when NOT to use it or compare with other siblings, but the intent is clear enough.
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 serves a distinct analysis layer: market regime, launch lists, graduation/rug event lists, per-mint risk cards, creator reputation, and wallet profiling. Even the demo tool (sample_mint) is clearly framed as a preview of mint_risk_card rather than a competing endpoint.
All tool names follow the same snake_case, descriptive noun-phrase pattern (creator_reputation, mint_risk_card, recent_launches). There is no mixing of verb styles or camelCase, making the toolset predictable for an agent.
Eight tools is well within the ideal range and each tool covers a meaningful slice of the pump.fun risk-analysis domain. No tool feels redundant or purely cosmetic.
The set covers the full workflow: market context, recent launches, graduation and rug outcomes, per-mint deep dives, creator history, and wallet classification. A user can trace a launch from listing through graduation or rug and then pull entity-level context without hitting dead ends.