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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds value by explaining the output structure (includes resources, specific fields to examine) and the relationship to datastore_query. 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?

Two efficient sentences: first states purpose, second provides actionable guidance on using the output. No unnecessary words, clearly front-loaded.

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 simple read-only tool with one parameter and no output schema, the description is complete. It explains what the tool returns and key fields to use, covering the user's likely information need. Annotations cover safety, and the description fills the gap left by the lack of output 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?

Only one parameter 'id' with schema description covering its type and format. The description reiterates 'by id or slug', which is consistent but adds minimal extra meaning beyond the schema. Baseline 3 due to 100% schema coverage.

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?

Description clearly states the tool retrieves a full Jersey dataset record by id or slug, including resources. It uses specific verbs (get/retrieve) and distinguishes from sibling tools like search_datasets and datastore_query by focusing on detailed single-record retrieval.

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 some guidance on next steps (using datastore_query) but does not explicitly state when to use this tool over alternatives like search_datasets or datastore_query. The mention of 'read each resource's id, url, datastore_active flag' implies use for obtaining dataset details, but lacks explicit context on when not to use it.

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