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Marcus-Rug-Intel

Rug Munch Intelligence

get_serial_ruggers

Identify serial rug pull deployers by cross-referencing known watchlists to assess token risk before transactions.

Instructions

Known serial rug deployer watchlist. Cross-reference before trusting new tokens. Cost: $0.02.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
min_tokensNoMin tokens deployed to qualify
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden. It discloses the cost ('Cost: $0.02'), which is valuable behavioral information. However, it doesn't mention rate limits, authentication requirements, response format, whether this is a read-only operation, or any other behavioral traits. The description adds some value with the cost disclosure but leaves significant gaps in behavioral understanding.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is brief (two sentences) and front-loaded with the core purpose. The cost information is efficiently appended. No redundant information or unnecessary elaboration is present. However, the first sentence could be more precisely structured to clearly separate purpose from usage guidance.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a risk assessment tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the tool returns (list of deployers? risk scores? binary flag?), how results should be interpreted, or what 'serial rug deployer' means operationally. The cost disclosure helps but doesn't compensate for the missing behavioral and output context needed for effective tool use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% with one parameter fully documented in the schema. The description doesn't mention the 'min_tokens' parameter at all, nor does it provide any additional context about parameter usage, constraints, or implications. Since schema coverage is high, baseline is 3 even without parameter information in the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool provides a 'serial rug deployer watchlist' for 'cross-reference before trusting new tokens', which gives a general purpose (identifying risky token deployers). However, it's somewhat vague about the exact function - it doesn't specify whether this returns a list, checks a specific token, or provides risk scores. It distinguishes from some siblings like 'get_api_status' but not clearly from other risk-checking tools like 'check_deployer_history' or 'check_token_risk'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions 'cross-reference before trusting new tokens' which provides some context for when to use it, but doesn't explicitly state when to choose this tool versus alternatives like 'check_deployer_history', 'check_token_risk', or 'marcus_forensics'. No guidance on prerequisites, limitations, or specific scenarios where this tool is preferred over siblings is provided.

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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