get_custom_components

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It transparently mentions that the output is automatically stored, returns an object ID, and can be referenced elsewhere. It also notes 'ComponentDefinitionList model or error message string.' It does not explicitly state read-only behavior, but the get semantics imply it. The disclosure of the object store side effect is an informative behavioral trait beyond what annotations would provide.

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 organized with the main purpose first, followed by parameter documentation, return type, and additional usage notes. It is somewhat verbose but each sentence adds value, such as storage behavior and object ID usage. It is appropriately sized for a tool with one parameter and a clear output.

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?

Despite no output schema, the description fully clarifies what the tool returns (ComponentDefinitionList model or error string) and how to further interact with the result (object store tools). It covers all necessary aspects for a simple list tool, including the optional parameter handling and the storage mechanism. No critical information is missing.

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%, but the description compensates by explaining the parameter 'haystack_version' in detail: 'Pass the same version as specified in the pipeline yaml's `dependencies` section.' This adds meaning beyond the schema, which only shows the type. The explanation is sufficient for understanding how to set it correctly.

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 tool's purpose: 'Get a list of all installed custom components.' This is a specific verb ('Get') and resource ('list of installed custom components'), and it distinguishes from siblings like list_custom_component_installations, which focuses on installation logs. The purpose is unambiguous and effectively differentiates from similar 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 implies usage context ('get a list of all installed custom components') but does not explicitly state when to prefer this tool over alternatives like search_component_definitions or get_component_definition. There is no guidance on exclusions or comparisons, though the purpose is clear. It gives basic instructions on the optional haystack_version parameter but lacks explicit when-to-use guidance.

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