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@blockchainacademics/mcp

@blockchainacademics/mcp

Official
by blockchainacademics
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

check_rugpull_risk

Assess composite rugpull risk by analyzing honeypot, LP lock, ownership renounce, contract verification, and team factors. Requires entity slug.

Instructions

Composite rugpull risk: honeypot + LP lock + ownership renounce + contract verification + team risk. Required: entity_slug. Pro tier.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "entity_slug": "<entity_slug>"
    },
    "name": "check_rugpull_risk"
  }
}

Input Schema

NameRequiredDescriptionDefault
entity_slugYesRequired. Target entity slug.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.1

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavior. It mentions the tool is composite and lists components, but it does not describe the output format (e.g., score, boolean, report), side effects, or authorization requirements beyond Pro tier. This leaves the agent with incomplete understanding of the tool's behavior.

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 extremely concise—a single sentence—and effectively lists the risk components. It sacrifices some detail for brevity but remains clear. It could be improved by adding a brief note on output, but given the simplicity, it earns a high score for conciseness.

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?

Even with 100% schema coverage and a clear purpose, the description fails to explain what the tool returns (no output schema) and lacks usage context relative to siblings. For a composite risk tool of moderate complexity, the description is incomplete.

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 coverage is 100% with a clear description for entity_slug ('Required. Target entity slug.'). The description repeats the requirement and implies it is an entity identifier, but adds no extra semantic meaning beyond what the schema already provides. Baseline of 3 is appropriate.

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

Purpose5/5

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

The description clearly states the tool computes a composite rugpull risk covering specific factors (honeypot, LP lock, ownership renounce, contract verification, team risk). It also mentions the required parameter and that it is a Pro tier feature, making the purpose highly specific and actionable.

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

Usage Guidelines3/5

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

The description indicates the need for an entity_slug and that it requires Pro tier, but it does not provide guidance on when to use this tool versus alternatives like check_memecoin_risk or check_exploit_history. No explicit when-to-use or when-not-to-use information is given.

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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