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

Annotations already establish readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint=false. The description adds useful domain semantics beyond that: it preserves draft review states, source references, and source-specific licensing, and it warns that depth classifications are hypotheses rather than ratings.

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?

Three short sentences with zero filler. The core purpose is front-loaded, followed by preservation behavior and a caveat about depth classifications.

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?

There is no output schema, and the description does provide useful return-content context around preserved states, references, licensing, and classification caveats. Still, for a four-parameter search tool with 0% schema description coverage, it leaves query, limit, offset, and enum semantics underexplained.

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 0%, so the description carries the full burden for four parameters. It hints that a single dataset must be selected, but it does not explain query, limit, or offset behavior, nor does it clarify the enum dataset values.

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 states a specific verb and resource: "Search one published Charitology dataset." This is clearer than a tautology and distinguishes search from the sibling read tools by verb, though it does not explicitly name those siblings as alternatives.

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?

The phrase "Search one published Charitology dataset" implies the use case and the required dataset selection. However, it gives no explicit when-to-use or when-not-to-use guidance relative to read_public_record or read_public_coverage.

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