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kvandre12-commits

WhaleSignal MCP

conviction_score

Get a 0-100 bullish/bearish conviction score for any ticker, fusing options flow, dark pool accumulation, dealer gamma, and congressional trades into an explainable score with per-signal breakdown and rationale.

Instructions

Composite 0-100 bullish/bearish conviction for a ticker.

Fuses options flow alerts, net premium, call/put volume, dark pool accumulation, dealer gamma regime and recent congressional trades into one explainable score with per-signal breakdown and a plain-English rationale.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the transparency burden and does it well: it states that the tool fuses multiple signals, outputs an explainable score, and provides a per-signal breakdown plus plain-English rationale. It does not cover data freshness, limitations, or failure behavior, but the core behavior is clearly conveyed.

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 tight and front-loaded: the main output phrase appears first, followed by a compact list of signal inputs and deliverables. Every phrase adds information and there is no filler.

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?

The description conveys purpose, composition, and output shape, and an output schema exists to handle the return-structure burden. The main omissions are an explicit statement of score direction (whether high values mean bullish or bearish) and more direct routing among the sibling tools.

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

Parameters2/5

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

The only parameter is ticker, and schema description coverage is 0%, so the description needed to add format, scope, or usage clarification. It only repeats the word 'ticker' and gives no guidance on ticker format, asset class, or how to specify symbols.

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 opening line defines a specific deliverable: a 0-100 bullish/bearish conviction score for a ticker. The description enumerates the fused signal sources, which clearly distinguishes it from the single-source siblings such as flow_alerts, dark_pool, and congress_trades.

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 implies use when an aggregate conviction signal is needed by listing the underlying components, but it never explicitly states when to choose this tool over flow_alerts, dark_pool, congress_trades, or market_pulse. No exclusions or decision conditions are provided.

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