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kvandre12-commits

WhaleSignal MCP

dark_pool

Retrieve recent dark pool prints for any stock ticker to identify large institutional trades hidden from public order books.

Instructions

Recent dark pool prints for a ticker.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
tickerYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

C2.4/5.0
Behavior1/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only says 'Recent dark pool prints for a ticker' and gives no information about data source, ordering, delay, read-only guarantees, rate limits, or what the output represents. This is effectively no behavioral 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 a single, front-loaded sentence with no filler. Every word ('Recent', 'dark pool prints', 'for a ticker') is relevant. It is appropriately concise for its content, even though that content is thin.

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 and a minimal description, this is incomplete. Even though the output schema covers return values, the description lacks usage guidance, parameter semantics for 'limit', and any behavioral context. It would not fully prepare an agent to call this tool correctly in a multi-tool environment.

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

Parameters1/5

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

Schema description coverage is 0%, so the description must explain the parameters. It implicitly mentions 'ticker' but completely ignores the 'limit' parameter, leaving the agent to guess what it controls (likely max number of prints, but this is not stated). The description adds no meaningful semantics beyond the schema.

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 states a specific resource (dark pool prints) and scope (a ticker), and it is clearly distinct from siblings like flow_alerts or conviction_score. However, it is a noun phrase rather than an explicit action statement (e.g., 'get recent dark pool prints'), so it leaves the verb to inference.

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 gives no guidance on when to use this tool versus alternatives. It does not mention any conditions, exclusions, or how it differs from sibling tools like flow_alerts or market_pulse, so an agent cannot route to it confidently.

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