log_learning

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

With no annotations provided, the description carries the burden of explaining side effects. It clearly states the write action ('Append') and the follow-up instruction to tell the user to commit learnings.md. It does not mention permissions, error handling, or return values, but for a simple logging tool this is reasonably transparent.

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 front-loaded with the core purpose and includes a clear directive. It is somewhat lengthy but every sentence serves a purpose: explaining the action, providing trigger examples, and offering follow-up guidance. It is structured as a coherent paragraph without 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?

The description covers the primary use case and trigger conditions well, but it lacks parameter-level detail and does not describe the return value or failure modes. Given the tool has 6 parameters with 0% schema coverage and no output schema, the description feels incomplete for an agent to invoke it confidently across all scenarios, though it is sufficient for the highlighted common cases.

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%, so the description must compensate. It provides examples of what to log (schema quirks, invalid formulas, etc.) but does not explain the individual parameters (title, pattern, trigger, example, promote_to) or how they map to the schema. The enum values for category and promote_to are not referenced or elaborated, leaving parameter semantics largely unexplained.

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 ('Append a newly discovered Workato recipe/API gotcha to learnings.md') with a specific verb and resource. It also distinguishes itself from the sibling tool workato_recipe_tips by explicitly referencing it as the known knowledge base, making its unique purpose clear.

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 explicit when-to-use guidance: 'CALL THIS AUTOMATICALLY when you hit a non-obvious behavior NOT already in workato_recipe_tips'. It lists concrete examples of applicable scenarios and even instructs the next step (tell user to commit), which serves as a usage workflow.

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