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makiichikawa

stock-mcp-server

by makiichikawa

screen_profit_turnaround_stocks

Screen stock symbols to identify companies that have transitioned from loss to profit, with optional market cap filters to refine results.

Instructions

Screen multiple stocks to find those that have turned from loss to profit

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolsYesArray of stock symbols to screen (e.g., ["AAPL", "GOOGL", "TSLA"])
maxMarketCapNoMaximum market capitalization filter (optional)
minMarketCapNoMinimum market capitalization filter (optional)
Install Server

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full behavioral disclosure burden. It does not state whether the operation is read-only, what output format is returned, how 'loss to profit' is defined or computed, what time period is considered, or whether there are any limits or 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 a single, focused sentence with no redundant wording. The core action and objective are front-loaded, and every word earns its place.

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?

There is no output schema and no annotation context, yet the description does not explain return values, screen criteria details, or edge cases. An agent can infer the basic purpose, but it lacks enough context to know what the tool will return or how to interpret the results.

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 description coverage is 100%, so the schema already documents all three parameters. The description adds no meaningful detail beyond the schema, such as how market cap filters interact with the screening logic or what units are expected, so the baseline score of 3 is appropriate.

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 clearly states a specific verb ('Screen'), a resource ('multiple stocks'), and the intended outcome ('find those that have turned from loss to profit'). It is understandable on its own, but it does not explicitly differentiate from the similarly named sibling analyze_profitability_turnaround, so it loses a point for sibling distinction.

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 analyze_profitability_turnaround or other screening/analysis siblings, and it provides no exclusions or conditions that would help an agent choose this tool over another.

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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