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

Goes well beyond the readOnlyHint annotation: reveals the bare-list return shape, that totalMarketCap is ALWAYS null (critical to avoid misreading results), that rows are sector+industry pairs requiring aggregation, blank-sector exclusion rules, single-sector industry assignment logic, the {error} dict on failure, and the data source with ~5,200 tickers. This is rich behavioral context that no structured field provides.

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?

Dense but every sentence earns its place, front-loading the scope distinction and following with return-shape and edge-case caveats. No filler; the ALL-CAPS emphasis on key gotchas (BARE LIST, PAIR, IS ALWAYS NULL) aids fast scanning.

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?

No output schema exists, so the description fully compensates by documenting the return structure, nullability, aggregation requirement, exclusion rules, and error shape. An agent has everything needed to call and interpret correctly.

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?

Zero parameters, so baseline is 4. The description correctly notes 'No arguments', sparing the agent from speculating about filters, which is the right content for a zero-param tool.

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?

States a specific verb+resource ('splits across sectors and industries') and explicitly scopes it as the whole catalog, not a portfolio. This differentiates it from portfolio-oriented siblings like get_portfolio_positions and ol_etf_lookthrough without the agent needing to open a schema.

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 names the alternative for portfolio-scoped data ('For a named portfolio use get_portfolio_positions'), routing the agent correctly. It does not enumerate other when-not conditions, but the catalog-vs-portfolio distinction is the primary decision an agent faces here.

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