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@blockchainacademics/mcp

@blockchainacademics/mcp

Official
by blockchainacademics
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

get_kol_influence

Calculate a KOL's influence score by combining reach, engagement, and historical pick accuracy. Supports rolling windows of 30 or 90 days.

Instructions

KOL influence score: reach × engagement × historical pick accuracy. Pro tier. Param: entity_slug (the KOL's canonical entity slug). Supported windows: 30d, 90d.

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": "get_kol_influence"
  }
}

Input Schema

NameRequiredDescriptionDefault
windowNoRolling window.
entity_slugYesEntity slug.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.1

TDQS

A4/5.0
Behavior3/5

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

No annotations provided, so description carries full burden. It explains the scoring formula and notes 'Pro tier' for access, but does not confirm read-only nature, indicate data sources, or disclose any side effects or limits. Adequate but not thorough.

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

Conciseness5/5

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

Two dense sentences with no filler. The purpose is front-loaded and every phrase serves a purpose. Highly efficient.

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

Completeness4/5

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

For a simple 2-parameter tool with high schema coverage and no output schema, the description covers the essential behavioral context (formula, premium tier, parameter hints). Missing details about return format (e.g., returns a number or score) but overall sufficient.

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

Parameters4/5

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

Schema coverage is 100% with minimal descriptions. The tool description adds value by specifying that entity_slug is 'the KOL's canonical entity slug' and explicitly listing supported window values ('30d, 90d'), which is not in the schema. This enhances parameter understanding beyond the bare schema.

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?

Description clearly states it computes a KOL influence score with a specific formula (reach × engagement × historical pick accuracy). Identifies the resource (KOL influence) and verb (get). Differentiates from numerous sibling tools which cover other metrics like fear/greed, news, prices, etc.

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?

Mentions 'Pro tier' indicating access restrictions and lists supported windows (30d, 90d), but does not explicitly state when to use this tool vs alternatives or when not to use it. Lacks exclusions.

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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