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bca-mcp

bca-mcp

by blockchainacademics
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_editorial_premium

Measures correlation between price returns and editorial coverage changes, identifying pre-coverage accumulation patterns over adjustable rolling windows.

Instructions

Correlation of price return to coverage delta (lagged -1 to +3 days). Pro tier. Measures pre-coverage accumulation edge. 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_editorial_premium"
  }
}

Input Schema

NameRequiredDescriptionDefault
entity_slugYesEntity slug.
windowNoRolling window. Supported windows: 30d, 90d.30d

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.1

TDQS

A3.5/5.0
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 behavioral traits. It explains the metric and lag, but does not mention read-only nature, rate limits, or any side effects. Lacks detail for complete transparency.

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?

The description is two sentences, front-loaded with the core purpose, and contains no unnecessary words. Every sentence adds value.

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

Completeness3/5

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

The tool has no output schema, so the description should hint at output format. It implies a numeric correlation but does not explicitly state what the return value looks like. Overall adequate for the low complexity, but leaves some ambiguity.

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%; parameters are already documented. The description adds that the window is rolling and reiterates supported windows, but does not significantly enhance meaning beyond schema descriptions. Baseline score 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 correlation between price return and coverage delta with specific lags, specifying it's Pro tier and the kind of edge it measures. It distinctly identifies the resource and action, differentiating from many sibling 'get_' tools.

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 mentions 'Pro tier' and 'Supported windows: 30d, 90d' but does not explicitly state when to use this tool over alternatives like get_history_correlation or when not to use it. Usage context is implied but not fully explicit.

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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