create_function

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

The description adds 'MUTATING' label and explains the dry-run behavior, which goes beyond annotations (readOnlyHint=false, openWorldHint=true). It provides critical context that the tool can be used for validation without side effects. No contradiction with annotations.

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, the first stating purpose and the second providing the key usage hint. It is front-loaded and contains no fluff, earning its place efficiently.

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?

While the description explains the tool's purpose and the dryRun behavior, it lacks information about return values (no output schema). For a mutating tool with 7 parameters, it could be more complete by hinting at what is returned (e.g., function ID). The schema fills some gaps, but the description misses this context.

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 100%, so baseline is 3. The description does not add new semantics for parameters beyond the schema, except for dryRun usage which is already mentioned in the description. Minimal added value for parameter understanding.

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 it creates a new Cognigy.AI Function and explains what functions are (custom code modules for integrations, scheduled jobs, computations). This distinguishes it from sibling create tools like create_node or create_intent, as it's specific to functions.

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 guidance on using dryRun parameter (set to false to actually create, default is validation). However, it does not mention when to use this tool vs alternatives like update_function or delete_function, missing explicit exclusion conditions.

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