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

With only readOnlyHint available, the description carries real behavioral weight: it warns the wording is not verified, ties verbatim status to a flag, mandates attribution, discloses 24h per-argument caching, and points caveats to the response's tool_notes. That is exactly the kind of context annotations cannot supply.

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 front-loaded: identity first, then the critical 'not verified' warning, then the response-shape contract. Every clause carries information, though the run-on structure with heavy emphasis makes it slightly hard to scan.

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?

With no output schema, the description correctly takes on the return-value burden, describing both response shapes, the 10-fact cap, the error shape, and where caveats live. An agent has everything needed to call it correctly and present results honestly.

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 genuine meaning: it explains that a query caps results at 10 while a bare category or empty call returns a single random pick, and it clarifies the category-or-error retry behavior. This goes beyond the schema's per-parameter field docs.

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 ('curated value-investing principle, historical fact or attributed paraphrase') and its source corpus, explicitly naming the authors covered. It also declares what the tool is NOT ('never a market signal'), which cleanly separates it from the market-data siblings like get_fundamentals or get_news.

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?

Gives clear context ('Pedagogical content only -- never a market signal') and implicitly routes by argument mode (query vs bare category vs no arguments). It does not name an alternative sibling tool or spell out when-not to call it, but the usage context is unambiguous for an agent.

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