Dataset Probe Hf

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

readOnlyHint=true already tells the agent this is a safe read, so the description carries a lower burden, but it adds almost nothing beyond that — it does not say what 'probing' returns, whether it fetches data or only metadata, or any auth/rate-limit context. The word 'pinned' only weakly signals the immutable-revision requirement.

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?

It is a single well-formed sentence with no filler, and the resource is front-loaded. It is efficient, though under-specified rather than overly verbose.

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 a required nested request object of five undocumented fields and no annotation depth, the description is too thin; the existing output schema means return values need not be explained, but the input semantics and purpose distinctions are still missing.

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 0% and the single parameter is a nested object with five sub-fields (hf_repo, hf_revision, hf_split, hf_config, sample_records) that are entirely undocumented. The description's mention of a 'pinned ... split' only faintly gestures at hf_revision and hf_split and does not compensate for the coverage gap.

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 names a verb ('probe') and resource ('configs and row mappings for a Hugging Face dataset split'), so the general domain is inferable. However, 'probe' is vague, and the definition does nothing to separate it from close siblings like dataset_inspect, dataset_validate, or dataset_search_hf.

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?

There is no statement of when to use this tool versus the many dataset siblings (dataset_prepare, dataset_fetch_hf, dataset_search_hf, dataset_validate, dataset_inspect, dataset_render_preview). No prerequisites, no exclusions, no conditions are provided.

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