Rug Munch Intelligence

get_social_osint

Analyze social infrastructure for crypto tokens to detect account recycling, domain age, and cross-reference with known scam infrastructure.

Instructions

Social infrastructure analysis: Twitter account recycling, domain age, Telegram group legitimacy, cross-references with known scam infrastructure. Cost: $0.06.

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": {
      "token_address": "<token_address>"
    },
    "name": "get_social_osint"
  }
}

Input Schema

Name	Required	Description	Default
`token_address`	Yes	Token address

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.1Mar 13, 2026

TDQS

C2.9/5.0

Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions a cost ($0.06) which is useful context, but doesn't describe what the analysis returns, whether it's a one-time or ongoing analysis, rate limits, authentication requirements, or what 'social infrastructure analysis' entails beyond the listed examples.

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 efficiently structured in two sentences: one describing the analysis scope and one stating the cost. It's appropriately sized for a single-parameter tool, though it could be more front-loaded with the core purpose.

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 tool with no annotations, no output schema, and complex social analysis functionality, the description is incomplete. It doesn't explain what the analysis returns, the format of results, error conditions, or how the listed examples (Twitter, Telegram, etc.) manifest in practice. The cost mention helps but doesn't compensate for missing behavioral context.

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%, so the schema already documents the single 'token_address' parameter. The description doesn't add any parameter-specific information beyond what's in the schema, such as format requirements or how the token address relates to the social analysis. Baseline 3 is appropriate when schema does the heavy lifting.

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 performs 'social infrastructure analysis' with specific examples (Twitter account recycling, domain age, Telegram group legitimacy, cross-references), which provides a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'get_token_intelligence' or 'marcus_forensics' that might also analyze token-related social data.

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. While it mentions a cost ($0.06), it doesn't specify use cases, prerequisites, or comparisons with sibling tools like 'check_token_risk' or 'get_token_intelligence' that might offer similar functionality.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.