harvest_labels

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

With no annotations, the description carries the full burden. It explains the tool's behavior (harvesting field metadata), the focus_cim option, and returns a detailed dictionary structure. It is clearly a read-only discovery operation, though it doesn't mention potential performance impacts or permission requirements.

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-organized with a brief intro, an Args list, and a Returns section. Every sentence provides necessary information without fluff, making it easy to scan and parse.

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 four optional parameters and no annotations, the description covers purpose, parameter semantics, and return payload adequately. It could include error scenarios or permission caveats, but it provides sufficient information for an agent to invoke 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 no parameter descriptions (0% coverage), so the description's Args section fully compensates by explaining each parameter: indexes, focus_cim, max_sample_events, and timeframe, including defaults and examples. This adds significant meaning beyond the schema.

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 discovers and harvests field labels, schemas, field names, types, sample values, and metadata from Splunk indexes. This is a specific verb+resource that distinguishes it from sibling tools like search_splunk or list_indexes.

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 context for when to use it ('to support DeepTempo training and evaluation') and mentions the CIM field option, but it does not explicitly contrast with alternatives like get_field_summary or state when not to use it. Usage is implied rather than exhaustively specified.

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