Market data: quote, fundamentals, and a snapshot

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

With no annotations, the description carries the full burden and does most of it well: it discloses parallel dual-provider fetching, that fields are compared and merged, that each item is provenance-labelled, and the exact data_provider envelope states (BOTH/TRADINGVIEW/FINVIZ/NONE) including the degradation case where data is not cross-verified. It omits cost/latency implications of hitting two providers and what an error response looks like beyond NONE.

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?

Front-loaded with the one-line purpose, then structured prose, then Args/Returns blocks that are easy to scan. Slightly verbose — the provider-parenthetical and the 84-field mention are dense — but every sentence adds information rather than restating the name.

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 single-ticker aggregation tool with one parameter, the definition covers what is fetched, how sources are reconciled, and how to interpret the provider envelope. Since an output schema exists, the Returns section is bonus context rather than a necessity. The main remaining gap is the absence of guidance on when a caller should prefer a sibling tool instead.

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?

Schema coverage is 0% for the single symbol parameter, so the description must compensate — and it does, supplying format examples (AAPL, BRK.B, BRK-B) and noting the ticker can be written for either source, which resolves the real ambiguity of dot-vs-dash class shares. It does not state validation rules or case sensitivity.

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 opening line states a specific verb and resource ("Dual-sourced quote and fundamentals for one US ticker") and the body enumerates exactly which fields are fetched and merged. It is clearly distinguishable from bulk/screening siblings, but it never names an alternative tool, so the differentiation is inferential rather than explicit.

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?

Usage is implied: one ticker, quote plus fundamentals, dual-source comparison. There is no explicit when-to-use versus siblings like stock_prices, market_snapshot, technical_analysis, or stock_peers — even though the description mentions peers and RSI as data it carries, which are their own dedicated tools. No exclusions or prerequisites are stated.

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