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

Annotations already cover read-only, idempotent, closed-world, non-destructive, so the description is free to spend its words on behavior: it discloses that the response is a broad multi-domain composite and that the 'analysis' block is generated commentary requiring a disclaimer when shown to the user. It does not mention latency, payload size, or cost, which matters for a call that fans out across many data domains.

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?

The scope summary is front-loaded in the first clause and, given that the tool spans eight or more data domains, the length is justified. However, the body is one long run-on sentence with stacked parentheticals, and the financials/dilution content is tacked on with 'Also includes' as an afterthought rather than being structured into the enumeration.

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 an output schema present, the description needn't enumerate return fields, and it still does enough by listing domains and mandating how the 'analysis' text must be presented to the user. The main remaining gap is sibling routing guidance for the many narrower tools that overlap with parts of this response.

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% and both parameters are documented with ranges and a default, so the schema carries the load. The description only indirectly touches parameterization ('unusual vs history' implying the look-back window) and never mentions insider_days explicitly, adding little beyond structured data — baseline 3 is appropriate.

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 opening line 'Everything that matters about one company in one call' plus the enumerated contents (insider signal, earnings countdown, volatility regime, trend vs moving averages, drawdown, analyst consensus, market backdrop, financials, dilution, written take) makes the resource and its composite nature unmistakable. It is clearly differentiated from narrow siblings like get_insider_signal, get_financials, and get_market_context because it explicitly bundles all of them.

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?

Example trigger phrases ('analyze X', 'should I look closer at X?', 'anything notable about X before earnings?') give concrete usage context, and the presentation instruction ('present it to the user, and say it is automated context, not investment advice') is actionable. It stops short of stating when NOT to use it, e.g. that a narrow question about insiders should go to get_insider_signal instead of this heavier aggregate call.

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