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Signal8 MCP Server

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Get Post-Earnings Movers

get_post_earnings_movers
Read-only

Identify stocks with significant price movements after earnings reports on a specific date. Returns price changes and earnings surprise data in one call.

Instructions

Get stocks that moved significantly after earnings reports on a given date. Returns pre-computed price changes with earnings surprise data in a single call — no need to chain get_earnings_calendar + get_historical_prices + get_quote per ticker. Includes preEarningsClose, currentPrice, changePct, EPS/revenue actuals vs estimates, and surprise percentages. Filter by minimum absolute % change threshold.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateYesEarnings date to check (YYYY-MM-DD)
limitNoMaximum results to return (default 25, max 100)
minChangePctNoMinimum absolute % price change to include (default 5). Set to 0 for all.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
Behavior4/5

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

Annotations already indicate readOnlyHint=true. The description adds value by listing the returned fields (preEarningsClose, currentPrice, changePct, surprise data) and mentions the computation is pre-computed, setting expectations for a single-call retrieval without side effects.

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 concise, comprising three sentences that front-load the core purpose and quickly provide functional details. Every sentence adds value without repetition.

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

Completeness5/5

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

Given the presence of an output schema, the description adequately covers the tool's functionality. It explains the input parameters, the data returned, and the benefit over alternatives, making it complete for agent decision-making.

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% with descriptions for all three parameters. The description reiterates the minChangePct filter and default values but adds little new meaning beyond the schema. The listing of return fields does not directly enhance parameter understanding.

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 retrieves stocks that moved significantly after earnings on a given date, specifying the verb 'get' and resource 'post-earnings movers'. It distinguishes from chaining multiple calls, providing a clear use case.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains when to use this tool (to avoid chaining get_earnings_calendar, get_historical_prices, and get_quote) and implies alternatives but does not explicitly state when not to use it. The guidance is clear and helpful.

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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