stocks.quote

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

No annotations are provided, so the description fully covers behavioral aspects: it discloses that data is delayed (delayed=true), specifies the timeframe (end-of-day), and lists the return fields. No contradictions or hidden semantics.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences efficiently convey purpose, scope, and constraints. First sentence lists fields, second warns about delay and usage, third credits provider. No redundant information.

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

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

For a simple one-parameter tool with no output schema, the description is well-rounded: it explains input, output, data quality, and intended use. Minor gap: no mention of error conditions (e.g., invalid ticker), but overall sufficient.

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

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

The input schema already fully describes the ticker parameter with maxLength and example. The description adds value by specifying 'US-listed ticker' with examples (AAPL, MSFT, BRK.B) and contextualizing the output fields, which compensates for the lack of output schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it provides the latest daily stock quote for a US-listed ticker, listing specific fields like open/high/low/close, volume, etc. It distinguishes itself from sibling tools like crypto.token-price or finance.company-facts by focusing on US stock quotes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states the data is end-of-day and delayed, intended for daily snapshots and post-close analysis, not real-time trading. This provides clear when-to-use and when-not-to-use guidance. Also credits the data source (Massive/Polygon.io).

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