update_llm

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

Annotations already indicate it's mutating (readOnlyHint=false), idempotent (idempotentHint=true), and not destructive (destructiveHint=false). The description adds value by explicitly labeling it as 'MUTATING' and explaining the dryRun parameter behavior (validates by default, set to false to actually update). This is helpful beyond 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 exceptionally concise: two sentences that efficiently convey the tool's purpose and a critical usage note. No wasted words; every sentence earns its place.

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 tool with 7 parameters, a nested object, and no output schema, the description covers the essential behavioral information (mutating, dryRun). It does not discuss return values or permissions, but the annotations fill in some gaps. Adequate for use.

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 coverage is 100%, so each parameter already has a description. The description briefly lists some parameters (name, description, credentials, provider settings) but does not add significant new meaning. It omits dryRun and isDefault, which are covered by schema. Baseline 3 is appropriate.

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 verb 'Updates' and the resource 'existing Cognigy.AI large language model configuration', listing specific fields that can be changed. It is easily distinguishable from sibling tools like create_llm, delete_llm, clone_llm, etc.

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 says 'Use this to change name, description, credentials, or provider settings', providing clear context for when to use this tool. It does not explicitly exclude alternative tools, but given the sibling list, the purpose is well-defined.

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