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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description still adds real context beyond them: sign-correction of short-book returns, disclosure rules, what is withheld and why, and a not-advice notice — useful behavioral detail about the content returned.

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?

It is a single dense sentence followed by one usage sentence — front-loaded and mostly waste-free. The enumeration is long but each item earns its place by telling the agent what the reference contains.

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 carries the burden of explaining returns, and it does so by listing the categories of methodology content available. An agent knows what it will get without needing a schema, though exact structure/format remains unstated.

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 tool takes zero parameters, so per the rubric the baseline is 4. Nothing in the schema needs elaboration and the description correctly does not invent parameter semantics.

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 states a clear subject: the measurement methodology behind every fund figure, enumerating coverage areas (index construction, since-inception returns, status meanings, disclosure rules, URLs). This cleanly distinguishes it in spirit from get_fund/get_fund_history, though it never names those siblings as the data-vs-methodology boundary.

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?

It gives an explicit trigger: 'Use it when a user asks how a fund figure is measured or what a status means.' That is clear context for invocation, but it does not state when NOT to use it or point at an alternative tool for raw fund data.

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