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tanmaymish

MarketPulse MCP

by tanmaymish

portfolio_analysis

Compute portfolio P&L, individual stock performance, weights, concentration risk, and winners/losers. Input holdings as symbol, quantity, buy price.

Instructions

Analyze a stock portfolio — P&L, weights, risk. [PRO]

Provide your holdings and get total P&L, individual stock performance, portfolio weights, concentration risk, winners and losers.

Args: holdings: JSON string of holdings array. Each holding needs: symbol, quantity, buy_price. Example: '[{"symbol":"RELIANCE","quantity":10,"buy_price":2500}, {"symbol":"TCS","quantity":5,"buy_price":3800}]'

Examples: portfolio_analysis('[{"symbol":"RELIANCE","quantity":10,"buy_price":2500}]') portfolio_analysis('[{"symbol":"AAPL","quantity":5,"buy_price":150}, {"symbol":"MSFT","quantity":3,"buy_price":380}]')

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
holdingsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the transparency burden. It details the input format and expected outputs, but does not explicitly state that it is read-only, mention authentication requirements, or note limitations. The examples add some context, but not comprehensive behavioral disclosure.

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 well-structured with a concise purpose line, a brief explanation, an Args section, and examples. Every sentence adds value, and the format is front-loaded and easy to parse.

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 single parameter is thoroughly documented, an output schema exists, and the purpose is clearly explained, the description is sufficient for an agent to select and invoke the tool correctly. The additional listing of outputs and examples further enhance completeness.

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

Parameters5/5

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

The schema only defines 'holdings' as a string with zero description coverage. The description fully compensates by specifying the exact JSON structure, required fields (symbol, quantity, buy_price), and providing two clear examples. This is exemplary parameter documentation.

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 the tool analyzes a stock portfolio, listing specific outputs (P&L, weights, risk). It uses a specific verb+resource but does not differentiate from the sibling tool 'analyze_portfolio' which likely has a similar purpose.

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 usage via 'Provide your holdings and get...' and includes examples, but it does not explicitly state when to use this tool over alternatives like analyze_portfolio or provide exclusions. This is adequate but not 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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