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

Beyond annotations that already declare this as read-only and idempotent, the description adds valuable context: the underlying backend (data.gov.au CKAN Action API), that no auth is required, and the exact return fields. It does not mention pagination or rate limits, but the annotations and output schema carry most of the safety burden.

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 sentences with no filler: purpose and outputs first, helper guidance second, backend/auth context last. Every sentence earns its place.

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?

The description is largely complete given the output schema and annotations, but it contains a broken sibling-tool reference and fails to explicitly contrast with datasets.detail. This makes the guidance slightly unreliable despite otherwise good coverage.

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%, and each parameter already has clear descriptions with examples. The description reinforces the organization filter via the helper-tool reference, but adds no new meaning beyond what the schema provides; baseline 3 is appropriate.

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 ('Search'), a specific resource ('Australian Government open data catalog'), and specific filter dimensions (free text, publishing agency). It also lists the returned fields, making the tool's function unmistakable and distinguishing it from the sibling datasets.detail tool.

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 tells the agent to use au-data-gov.organization_search for agency slugs, but the actual sibling tool is named au-data-gov.reference.organization_search — this is a misleading reference that could cause the agent to call a nonexistent tool. It also does not clarify when to prefer this search over au-data-gov.datasets.detail or the reference tools.

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