get_learnings

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

No annotations are provided, so the description carries the burden. It clearly states the operation is a read ('Read the... log'), which implies a non-destructive action. It also provides context about the data source ('accumulated team discoveries not yet promoted'), setting expectations about the content. However, it does not explicitly mention that it is read-only or describe the return format, which would add further transparency.

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 two sentences, front-loaded with the verb and resource, then adds context and usage guidance. Every sentence earns its place with 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?

Given the tool's simplicity (one optional parameter, no output schema), the description is complete. It explains what the tool does, the nature of the data, and when to use it. The guidance to consult it alongside workato_recipe_tips covers practical usage, and no missing information prevents an agent from selecting and invoking the tool 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?

The schema has one optional 'category' parameter with enum values but zero description coverage. The description compensates by explaining the parameter's purpose: 'Optionally filter to one category.' This adds significant meaning beyond the bare schema, though it does not enumerate the specific categories or provide additional syntax details.

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 states a specific verb and resource: 'Read the learnings.md intake log'. It also distinguishes the tool from siblings by clarifying that these are 'accumulated team discoveries not yet promoted into workato_recipe_tips', and references workato_recipe_tips as a related tool. This clearly sets it apart from similar read tools.

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 gives usage context: 'Consult this alongside workato_recipe_tips before building a recipe.' It also implies when to use this vs. the promoted log by saying 'not yet promoted', indicating that workato_recipe_tips contains the promoted content. This provides clear guidance on when and how to use the tool.

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