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

Annotations already declare readOnlyHint, idempotentHint, non-destructive, and closed-world, so safety is covered. The description adds genuine context beyond them: the size and composition of the corpus (531 classifiers, 161 human vs 370 auto per the source enum) and which classifier fields are searched, which helps an agent predict result character. It omits result limits, ranking, and whether an empty response is possible, but the substantive additions outweigh the gaps.

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 short sentences, front-loaded with the action and its search scope, then the corpus scale, then the workflow directive. Every sentence carries distinct information (action, matched fields, inventory, sequencing) with no repetition.

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 discovery tool with full schema coverage and read-only annotations, the definition covers purpose, scope, inventory size, and workflow position. The main omission is any hint of what a result looks like (no output schema exists) or how many classifiers are typically returned, though that is a minor gap for a keyword lookup.

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 both the `source` enum values and the `keyword` match behavior are already documented in structured fields; the description largely restates the keyword field semantics. It adds no syntax, tokenization, or multi-word matching guidance beyond what the schema provides, so the baseline 3 applies. Note the schema marks keyword 'Required' while the supplied required-parameter count is 0 — the description does not clarify this either way.

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 verb and resource ('Search for available binary classifiers by keyword') and immediately narrows scope by naming the fields matched (classifier name, human-readable name, description). The corpus description (531 classifiers over SEC filings, with example themes) lets an agent distinguish this discovery tool from screening or semantic-search siblings without opening any 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?

Explicitly routes the agent in workflow terms: 'Use this tool first to discover classifier names before screening,' which gives a clear when-to-use condition tied to a downstream step. It does not name any alternative tool or state when not to use it (e.g., for free-text conceptual search), so it stops short of full alternative routing.

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