agent-toolbelt

Valuation Snapshot

valuation_snapshot

Analyze stock valuation by calculating key financial ratios and determining if a stock is cheap, fair, or expensive with specific buy zone pricing.

Instructions

Assess whether a stock is cheap, fair, or expensive. Pulls P/E, P/S, EV/EBITDA, FCF yield, ROE, and margins, then synthesizes them into a verdict with a specific buy zone price level.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "ticker": "<ticker>"
    },
    "name": "valuation_snapshot"
  }
}

Input Schema

Name	Required	Description	Default
`ticker`	Yes	Stock ticker symbol (e.g. NVDA, AAPL, MSFT)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Mar 30, 2026

TDQS

A4/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden and successfully discloses key behaviors: it pulls specific financial multiples, performs synthesis (not just raw data), and returns a structured verdict with a specific buy zone price level. Missing minor operational details like data freshness or calculation methodology prevents a 5.

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?

Two sentences with zero waste. First sentence establishes the valuation spectrum assessment; second details the specific metrics pulled and the synthesis methodology. Information density is high with no filler words or redundant restatements of the tool name.

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

Completeness4/5

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

Given the absence of an output schema, the description effectively compensates by detailing the return structure (specific metrics, verdict, buy zone price). It adequately covers the tool's functionality for a single-parameter analysis tool, though mentioning data sources or caching behavior would provide full completeness.

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 'ticker' fully documented including examples. The description focuses entirely on behavior/output rather than parameters, which is acceptable given the schema's completeness. Baseline score of 3 is appropriate as the description neither adds to nor detracts from 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?

Description uses specific verb 'Assess' with clear resource (stock valuation) and explicitly defines the three possible outcomes (cheap, fair, expensive). It distinguishes from siblings like 'stock_thesis' and 'earnings_analysis' by specifying valuation multiples (P/E, EV/EBITDA) and quantitative synthesis rather than qualitative thesis or earnings-specific analysis.

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 through specificity (valuation screening, buy zone identification) but lacks explicit guidance on when to prefer this over 'stock_thesis' for comprehensive analysis or 'bear_vs_bull' for sentiment. No 'when-not-to-use' or prerequisite conditions are mentioned.

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