MeritValue

Expected return at a given price

get_expected_return

Read-only

At a price you supply, the annual return the base case implies. MeritValue holds no market-data licence, so it never returns a live quote — the caller must provide the price. Ask the user for it, or have them check a broker; do not guess one, and do not present a guessed price as a real one.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`price`	Yes	Share price to test, in the company's reporting currency.
`ticker`	Yes	Ticker symbol, e.g. AAPL. Case-insensitive.

Output Schema

TableJSON Schema

Name	Required	Description
`price`	Yes	Echoed back — the price you supplied, never a quote.
`ticker`	Yes
`refused`	No	Present when the flagship DCF doesn't apply. A refusal is a result — report it, don't retry.
`currency`	No
`disclaimer`	No
`assumptions`	No
`engine_version`	Yes	Engine build that produced these figures.
`expected_return`	Yes	Annual return the base case implies, as a fraction. Null when it can't be solved.

TDQS

A4.7/5.0

Behavior5/5

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

The description goes beyond annotations by explaining that MeritValue holds no market-data licence and never returns a live quote, so the caller must provide the price. It also warns against presenting a guessed price as real, adding meaningful behavioral context that is not in the readOnlyHint or openWorldHint flags.

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 three sentences, front-loaded with the primary purpose, followed by the rationale for the price requirement, and ends with a clear usage instruction. Every sentence earns its place with no redundant content.

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?

The tool is simple, with annotations covering read-only behavior, a complete schema, and an output schema present. The description covers the essential nuance (no live data, caller-provided price) and is fully sufficient for an agent to use the tool correctly.

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

Parameters4/5

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

While the schema already covers both parameters (100% coverage), the description adds semantic context to the price parameter by emphasizing it must be supplied externally and not guessed. This extra guidance clarifies the parameter's role beyond its type and description.

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's purpose: given a price, it returns the annual return implied by the base case. This is a specific verb+resource, and it distinguishes itself from siblings like get_intrinsic_value by focusing on return at a supplied price rather than valuation.

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 explicitly tells the caller that they must supply the price and instructs them to ask the user or check a broker, not to guess. It does not mention alternatives or explicitly say 'use this instead of X', but it gives clear context on how to obtain the required input.

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

All MeritValue tools Inspect

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TDQS

A4.4/5.0

Disambiguation4/5

Each tool has a distinct primary purpose: searching, fundamentals, quality, valuation, expected return, thesis, and screening. The only minor overlap is between get_business_quality and get_thesis, but their descriptions clearly differentiate (quality metrics vs. combined thesis). Overall, agents can reliably select the right tool with minimal confusion.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with lowercase and underscores: get_*, screen_undervalued, search_companies. The verbs are descriptive and uniform, and the one adjective (undervalued) doesn't break the pattern. This is highly predictable.

Tool Count5/5

Seven tools is well within the ideal range for a specialized financial analysis server. Each tool covers a distinct core function without redundancy or bloat, making the set easy to navigate and maintain.

Completeness5/5

The tool set covers the full workflow for fundamental analysis: resolving companies, retrieving raw fundamentals, assessing quality, valuing the business, computing expected returns, generating theses, and screening for undervalued names. The deliberate absence of market data is documented, so there are no dead ends.

Resources

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