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run_dcf_valuation

Run a Discounted Cash Flow model on live free cash flows to estimate a stock's intrinsic value.

Instructions

Runs a Discounted Cash Flow (DCF) model to estimate the intrinsic value of a stock using live free cash flows.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesThe stock ticker symbol
growthRateNoProjected annual growth rate (percentage)
discountRateNoDiscount rate (WACC percentage)
Behavior2/5

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

With no annotations provided, the description carries the full burden of disclosing behavioral traits. It mentions 'live free cash flows' which suggests dynamic data retrieval, but it doesn't disclose potential side effects, data source dependencies, error handling, or whether it's a pure read operation. The agent is left with significant uncertainty.

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 sentence that front-loads the action and stays focused on the core purpose. Every word is meaningful, and there is no redundant or extraneous text.

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?

The tool has no output schema and no annotations, leaving the description as the only source of context. It never states what the tool returns, what happens if optional parameters are omitted, or what assumptions are baked into the model. This is insufficient for a financial modeling tool with three parameters.

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%: each parameter has a description (e.g., growthRate: 'Projected annual growth rate (percentage)'). The tool description adds no additional meaning beyond the schema, so the baseline of 3 applies. It does not clarify format nuances like whether percentages are expressed as decimals or whole numbers.

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 identifies the tool's function: running a Discounted Cash Flow model to estimate intrinsic value using live free cash flows. This specific verb-resource combination distinguishes it from sibling analytical tools like get_stock_price or calculate_financial_ratios.

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 explicit guidance on when to use this tool versus alternatives. It does not mention when not to use it, prerequisites, or how it fits into an investment analysis workflow. While the purpose is clear, the lack of comparative context leaves the agent to infer usage.

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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