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

Annotations already cover read-only, idempotent, closed-world, non-destructive, so the description is free to add the parts annotations cannot: fuzzy matching behavior, the usable ref formats (full uuid:// or bare id), and the important note that `dataset_key` may be null for the platform sample. That null-handling caveat is exactly the kind of context that prevents misinterpretation. It doesn't cover pagination/truncation behavior when `limit` is hit.

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, front-loaded with purpose before the chaining detail. The uuid:///dataset_key sentences are dense but each carries operational value for constructing dataset_ref; no filler.

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?

With no output schema, the description steps in to describe the returned reference field and its null edge case, and with only 2 fully-documented params plus safety annotations there is nothing else an agent needs to call this 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 baseline is 3, but the description adds 'fuzzy matching' semantics for `search` that the schema's 'Search by name, description, or tags' does not convey. `limit` gets no additional treatment, hence not a 5.

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?

States a specific verb ('List and search') and resource ('your uploaded datasets'), plus the matching semantics (fuzzy on name, description, tags). This cleanly distinguishes it from datasets_upload and from the path_* consumers it feeds.

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?

Explains what to do with the result — use the `usage` field (uuid:// reference) as dataset_ref in path_resolver and path_tool_run — which gives concrete downstream usage context. It stops short of explicit when-not-to-use guidance or naming an alternative listing tool.

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