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Marcus-Rug-Intel

Rug Munch Intelligence

check_blacklist

Verify if a cryptocurrency token has been flagged by community-sourced intelligence to detect potential scams before transactions.

Instructions

Check if a token is community-flagged. Community-sourced intelligence with reputation-weighted flags. Cost: $0.02.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
token_addressYes
chainNosolana
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'community-sourced intelligence' and a cost, but doesn't cover critical aspects like rate limits, authentication needs, error handling, or what 'community-flagged' entails (e.g., severity levels, confidence scores). For a tool with financial implications and no annotations, this is inadequate.

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 concise and front-loaded, with three sentences that each add value: purpose, data source, and cost. There's no wasted text, and it efficiently communicates key information. However, it could be slightly more structured (e.g., separating cost into a separate note).

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?

Given the complexity (financial tool with community data), lack of annotations, no output schema, and 0% schema description coverage, the description is incomplete. It misses details on output format, error cases, usage limits, and how results should be interpreted. The cost mention is helpful but doesn't compensate for other gaps.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for undocumented parameters. It doesn't explain what 'token_address' or 'chain' represent, their formats, or examples. The mention of 'token' implies 'token_address' is a token identifier, but this is vague. With 2 parameters and no schema descriptions, the description adds minimal semantic value.

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

Purpose4/5

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

The description clearly states the tool's purpose: 'Check if a token is community-flagged.' It specifies the verb ('check') and resource ('token'), and mentions the data source ('community-sourced intelligence with reputation-weighted flags'). However, it doesn't explicitly differentiate from sibling tools like 'check_token_risk' or 'check_token_risk_premium', which appear to serve similar risk assessment functions.

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 provides no guidance on when to use this tool versus alternatives. It mentions a cost ('Cost: $0.02'), which might imply usage considerations, but doesn't specify scenarios, prerequisites, or exclusions. With multiple sibling tools for token risk assessment (e.g., 'check_token_risk', 'check_batch_risk'), the lack of differentiation is a significant gap.

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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