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

Annotations only declare a safe read of a closed world; the description adds real substance with the valuation methodology ('that day's close (adjusted for share splits only) × the shares outstanding at that date from SEC filings'), units (USD, weights as fractions), and the fact that the last point is today's. It omits any note on refresh cadence, data latency, or cost, so it falls just short of a 5.

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-loads what is returned and the trigger condition before the methodology digression, which is the right order. Sentences are long and dense with parentheticals, and the `view: 'map'` behaviour is effectively stated twice, so there is mild redundancy, but no filler.

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 return-shape burden itself and does so: it names the series fields, the map fields, units, and the time granularity (daily up to a year, weekly over five years). It also pre-empts a likely misreading by explaining that `enteredOn` denotes an IPO rather than a data gap, which is exactly the kind of edge case an agent would otherwise bungle.

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 meaning beyond the schema by tying the parameters together — how `view: 'map'` pairs with `date`, how `sector` switches the breakdown from segment-level to company-level, and how `range` drives point spacing. It still repeats rather than extends the schema's segment enumeration, keeping it out of 5 territory.

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?

Opens with a specific verb and resource ('Returns the tracked companies as one market over time: combined market cap, the weight of each segment or company, and traded dollar volume') and then distinguishes its two modes. It is clearly separable from siblings like get_market_overview and get_price_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?

States an explicit trigger ('Use it when the user asks how the sector, a segment or a company's weight has changed over a period, or where trading volume is going') and names the alternative for the near-neighbour case ('For today's snapshot, use get_market_overview'). Both when-to-use and the routing exclusion are present.

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