distillery_update

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

No annotations are provided, so the description carries the full burden. It clearly describes success and error return shapes, including error codes like NOT_FOUND and INVALID_PARAMS. It also implies partial-update semantics by saying 'one or more fields'. However, it does not explicitly state that non-provided fields remain unchanged, and it does not detail permission or validation behavior beyond error codes. Still, it gives substantial behavioral context for a mutation tool.

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 well-structured with clear sections (USE WHEN, PARAMS, RETURNS, RELATED). It front-loads the core purpose and usage, then enumerates all parameters in a compact list, followed by return formats and related tools. Every sentence contributes valuable information with no filler.

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 11 parameters, no output schema, and no annotations, the description covers all essential information: parameter names and valid values, return formats, error codes, the requirement of at least one updatable field, and relationships to sibling tools. An agent has everything needed to call the tool correctly without further research.

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 fully explain each parameter. It does so by listing every parameter with its type, purpose, and valid enum values (e.g., for entry_type, status, verification). This adds meaningful semantics that the schema alone cannot convey.

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 ('Update') and a clear resource ('existing knowledge entry'), and it explicitly distinguishes itself from sibling tools like distillery_correct (for superseding) and distillery_get (for reading). This removes ambiguity about when this tool applies.

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 'USE WHEN' section explicitly tells the agent when to use the tool (modifying fields) and even specifies a precondition (at least one updatable field must be provided). The RELATED section names the alternative tool (distillery_correct) and the condition that selects it, leaving no ambiguity.

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