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

Annotations already cover the safety profile (readOnly, idempotent, openWorld, non-destructive), so the description's job is to add context beyond that. It does: it discloses the enumeration of sources read, the existence of a plain-language mode, and how reading_level interacts with that mode. It stops short of describing pagination, latency, or output shape, which keeps it from 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-loaded with the data scope, then triggers, then the exclusion — a sound ordering. It is compact, though the trailing 'Args: entity; since.' duplicates the schema and the fragment-heavy style costs a little readability.

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 telling the agent what comes back, and it does so by enumerating the covered sources. Combined with annotations covering safety and 100% schema coverage, an agent has enough to call this correctly; only return-format detail is absent.

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 description coverage is 100%, so every parameter (since, entity, reading_level, response_mode) is already documented in the schema. The description's 'Args: entity; since.' and its 'response_mode=plain for beginners' note largely restate schema content, adding only a hint of intent. Baseline 3 is appropriate when the schema does the heavy lifting.

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 names a specific verb+resource ('what has happened for a company since a date') and enumerates exactly what the read covers: earnings, filings and 8-K events, insider trades, capital returns, price move. It also distinguishes itself from the sibling get_thesis by framing its scope as a delta since a date rather than a standing case.

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 concrete trigger utterances ('what changed with X; catch me up on X') and an explicit exclusion with the correct alternative ('Not for: the standing case → get_thesis'). Both the when and the when-not are stated, so nothing is left to inference.

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