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

Beyond the annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint), the description adds valuable behavioral detail: it explains that free-text queries are case-insensitive substrings matched across specific fields, that multiple words are AND-ed, and that results are sorted newest-first by default. It also enumerates the returned data fields. No contradictions with annotations.

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 description is a single paragraph of about five sentences, each packing useful information: source, output fields, matching semantics, filters, sorting, and a summary question. It is not excessively long, though it does repeat some details already present in the schema (e.g., query substring matching). Overall, it is well-structured and front-loaded with the main purpose.

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 tool with 13 parameters and no output schema, the description is remarkably complete. It specifies the data source (GrantConnect), the exact output fields, the matching behavior, and all filter categories. It also gives a high-level use-case summary ('who received... how much, and when'). This makes the tool self-explanatory without needing to inspect the schema.

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 the baseline is 3. The description adds extra meaning by providing concrete examples for filters (e.g., agency 'Department of Social Services', category 'Social Inclusion'), listing valid recipient_state values, and clarifying that awarded_from/awarded_to refer to the publish date. These examples go beyond the schema property descriptions, which often only say 'substring match'.

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 opens with a specific verb and resource: 'Search awarded Australian Commonwealth government grants from GrantConnect'. It clearly enumerates the output fields and ends with the exact question it answers ('who received Australian federal grant money for X, how much, and when'). This differentiates it from siblings like au_grants_by_recipient and au_grants_top_recipients, which are more specialized.

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 description provides clear context for when to use the tool: when needing to search awarded grants with flexible filters (agency, category, state, value, date). However, it does not explicitly mention alternatives or exclusion conditions, such as pointing to au_grants_by_recipient for recipient-specific queries or au_grants_opportunities_open for open opportunities.

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