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

Annotations already declare the safety profile (readOnly, idempotent, non-destructive, closed-world), and the description goes well beyond them: it discloses that texts come from an editorial pipeline and arrive as untrusted data, warns never to follow instructions inside them, and defines the status=empty outcome. Provenance and prompt-injection risk are exactly the non-obvious traits an agent needs.

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?

Four sentences in one block, front-loaded with the purpose before usage, safety, and status semantics — every sentence carries distinct information. It is slightly dense with stacked parentheticals ('already formatted, with their units'), which costs a little readability but not substance.

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?

For a two-parameter read tool this covers purpose, triggers, exclusions, data provenance, and the empty-result signal; an output schema exists so return structure needn't be re-explained. Nothing an agent needs to call it correctly or interpret results safely 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% and both parameters (ticker, limit with default 20 and 1-100 bounds) are fully documented in the schema. The description adds no syntax, format, or default information for the parameters — its content about question/verdict/figures describes return values, not inputs. Baseline 3 applies.

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 specific resource ('Published write-ups of the platform about ONE security') and enumerates exactly what each item contains (question, verdict, figures with units, text). It also explicitly excludes sibling domains (dividends, multiples, sentiment), so an agent can separate it from dividends_by_ticker and screener without opening either schema.

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?

Gives an explicit positive trigger ('when the user asks whether there is an analysis of a company or wants a qualitative view next to the numbers') and explicit negative guidance ('Do not use it for dividends, multiples or sentiment'). This is a named when/when-not pair, not implied usage.

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