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

Goes well beyond the readOnlyHint/openWorldHint annotations: it discloses the computation methodology (weighted average for buys, quantity-only reduction for sells, split/merge adjustment) and a data-quality taxonomy (reported/partial/unavailable) with legal reasons for missing prices. It also warns the agent not to assert an average price when basis is partial, which is genuinely actionable behavioral context.

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 core purpose, then methodology, then parameters, then return fields and caveats — a logical order with no filler. It is dense and the middle sentences run long, but each clause carries necessary 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?

There is no output schema, and the description compensates fully by enumerating the returned fields (avg_cost, held_shares, priced_shares, coverage_pct, buys, first_trade, last_trade) and explaining the basis semantics. For a two-parameter analytics tool, nothing an agent needs to call or interpret it is missing.

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: holder is a partial reporter name whose omission changes behavior to 'all holders with prices', and ticker selects a single stock. That is more than the schema's bare field descriptions provide.

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 precise verb and resource: computes a per-holder average purchase price for one stock, and describes the exact data source (5% large-holding report detailed change tables). An agent can immediately distinguish this from sibling tools like get_holders or get_holder_history.

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 states the scope rule (pass holder for one holder, omit for all priced holders) and an exclusions rule (executive/major-shareholder reports have no price and are not used). It does not name a sibling tool as an alternative when this data is unavailable, which keeps it below a 5.

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