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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds useful non-annotation context: the underlying source (HDX CKAN Action API) and that no auth is required. This meaningfully extends the agent's understanding of call prerequisites without contradicting the 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?

Three sentences, each earning its place: one for what the tool returns, one for how the result is consumed, and one for data source/auth. No filler or repeated schema content.

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 low-complexity read-only lookup with two fully documented optional parameters and an output schema, the description covers the essential workflow, source, and authentication. There is no meaningful missing context that would prevent an agent from selecting and invoking it correctly.

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%, so the input schema already documents both 'limit' and 'query'. The description restates the query behavior ('filtered by a name substring') and adds no details about limit syntax or defaults beyond the schema; therefore the 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 opens with a specific verb and resource ('List humanitarian organizations publishing data on HDX') and adds scope details (UN agencies, NGOs, governments, clusters, dataset count, optional name substring). It clearly differentiates this reference tool from dataset-search tools by noting its output slug feeds into hdx.dataset_search.

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?

It gives a concrete downstream use ('Use the returned slug as the organization filter for hdx.dataset_search'), which tells an agent why and how this list is used. It does not explicitly list when-not-to-use it or compare it with sibling reference tools such as hdx.reference.locations, so it stops short of full exclusion guidance.

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