creator_reputation
$0.02: creator reputation — look-ahead-safe stats over our full launch history, last 25 launches, live mints, recent insider funding.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes |
$0.02: creator reputation — look-ahead-safe stats over our full launch history, last 25 launches, live mints, recent insider funding.
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes |
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?
With no annotations provided, the description carries the behavioral disclosure burden. It adds useful context such as 'look-ahead-safe' and the specific data windows, plus the $0.02 cost. However, it does not explicitly state that the tool is read-only or describe how the stats are computed.
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 compact sentence that front-loads the core concept and cost, then uses a scannable list of data categories. Every phrase earns its place with 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?
The description lists the main data areas and is adequate for a simple one-parameter lookup. However, without an output schema or annotations, it does not explain return value structure, address format, or how this tool differs from sibling tools, so it is not fully 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 description coverage is 0%, and the only parameter, 'address', has no description beyond its title. The tool description never mentions the address parameter or its expected format, leaving the agent to infer it from the tool name.
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 identifies the resource as creator reputation and enumerates the data ranges it covers, making the tool's purpose clear. It lacks an explicit verb and does not differentiate it from sibling tools such as wallet_profile, so it is clear but not maximally precise.
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?
There is no guidance on when to use this tool versus alternatives. Sibling tools like wallet_profile, mint_risk_card, and recent_launches are not mentioned, and no when-not-to-use conditions are provided.
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.