list_datasets

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

No annotations are provided, so the description bears the full burden. It discloses the underlying transport (ISPF vs FTP) and the login requirement for ISPF, which are meaningful behavioral details. It does not discuss rate limits or error handling, but for a read-only list operation, this level of transparency is sufficient. The output schema likely covers return values, so no need to duplicate.

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?

The description is compact and well-organized: a one-sentence purpose, a brief usage note about transport and login, and a clear Args definition. Every sentence earns its place, with the most critical information (matching pattern) front-loaded. No filler or redundancy.

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 single-parameter list operation with an output schema, the description covers the essential aspects: what it lists, how to specify the pattern, and the operational prerequisites. It doesn't mention potential limitations (e.g., case sensitivity, session state for FTP), but these are minor and the core usage is fully explained.

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?

The schema itself has zero description coverage for the single 'pattern' parameter, but the description's Args section fully compensates: 'Fully-qualified dataset name with wildcards (``*`` matches any qualifier)'. This adds precise semantics that the schema lacks, including wildcard syntax and qualification format, making it easy for an agent to construct valid inputs.

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 clearly states the action: 'List MVS datasets whose name matches pattern' – a specific verb and resource. It also distinguishes from siblings like list_members (which lists members within a dataset) and get_dataset_info (which fetches info on a single dataset), leaving no ambiguity.

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 explains the transport mechanism (ISPF 3.4 or z/OS FTP) and the prerequisite that the TN3270 session must be logged in when using ISPF. This gives clear context on when the tool is usable. It doesn't explicitly mention alternatives or when not to use it, but the prerequisites and transport choice serve as adequate guidance.

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