Get Processing Providers

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

The description adds value beyond the readOnlyHint annotation by specifying that it returns algorithm counts and active status, not just a list of names. This gives the agent a clear expectation of what the tool does. It does not mention any limitations or side effects, but the annotation covers the safety aspect.

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 extremely concise: two sentences that are front-loaded with the core action and examples. Every word serves a purpose, with no redundancy or fluff.

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?

Given the tool has no parameters, is read-only (confirmed by annotation), and has an output schema (not shown but referenced), the description covers everything an agent needs: the resource, the information returned, and when to use it. It is complete for this simple tool.

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 tool has zero parameters, so the schema provides full coverage. The description does not need to explain any parameters. With 0 parameters, the baseline is 4, and the description meets this standard.

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'), the resource ('Processing providers'), and provides specific examples like native, gdal, grass. It also mentions the returned information (algorithm counts, active status), making the purpose unmistakable. It distinguishes from sibling tools like list_processing_algorithms.

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 explicitly tells when to use the tool: 'Use to diagnose missing algorithms.' This provides clear guidance on its intended context. While it doesn't mention when not to use it, the sibling tools cover specific cases, and the description is sufficient for an agent to decide.

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