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

With no annotations supplied, the description carries the full behavioral burden and does reasonably well: it discloses the data source (SEC filings), the cost model ('1 credit per company with filed figures'), the degradation behavior for tickers lacking a dated price (null valuation columns), and a definitional quirk (net debt negative means net cash). It does not address latency, partial-failure behavior when a ticker has no filing, or what happens for the un-priced columns' ranking.

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, front-loaded with the core capability and metric inventory, then the optional valuation path, then the credit cost. No filler, no restatement of the name, and every clause carries operational 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?

The tool is moderately complex (multi-ticker aggregation plus optional valuation input), and an output schema exists so return shape needn't be explained. The description covers scope, source, cost, and the null-valuation edge case. It stops just short of complete because it doesn't say whether metrics are quarterly-period or trailing, or how ranking is computed across columns.

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 100%, so the baseline is 3, but the description adds real meaning: the '2 to 10' cardinality is stated in prose even though the schema declares no minItems/maxItems, making the description the only source of that hard constraint. It also explains the payoff of the optional prices map (market cap and P/E) beyond the schema's shape-only text. It loses a point for not clarifying per-ticker price format tolerance beyond the schema's own example.

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 names a specific resource (SEC filing fundamentals for 2-10 companies side by side) and enumerates the exact metrics produced: revenue growth over four quarters, pretax margin, net income growth, diluted EPS growth, net debt, plus optional valuation columns. That is far more concrete than a generic 'compare' verb. It stops short of 5 because it never names the obvious sibling alternatives (compare_stocks, analyze_stock, financials), so an agent must infer the boundary itself.

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 context is implied rather than stated: the '2 to 10 companies' scope and the optional price/date mechanism signal a peer-comparison task. There is no explicit when-to-use-this-instead guidance against compare_stocks or financials, and no stated prerequisites. An agent can infer the use case but gets no routing rule.

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