splunk__query_examples

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

With no annotations provided, the description bears full burden. It transparently describes the output structure (JSON list with fields like area, spl, result_rows, etc.) and behavior (sorted by most recent first). No contradictions observed.

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, though the Args block adds some verbosity. Overall, every sentence adds value, and it is appropriately sized for the tool.

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 the tool has an output schema, the description need not explain return values in detail, but it does so anyway. It covers all necessary aspects: what the tool does, when to use it, parameter details, and output format. Complete for a query tool.

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 description must compensate. It does so by explaining both parameters: area with filtering guidance and example labels, and limit with default value. This adds meaningful context beyond the raw 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 returns example SPL queries from past investigations, using the specific verb 'Return' and resource 'example SPL queries'. It distinguishes from sibling tools by emphasizing that these examples are from past investigations in splunk.db, providing grounding for follow-up queries.

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 explicitly says 'Use this to ground follow-up queries in field names and patterns', providing clear usage context. However, it does not explicitly state when not to use or contrast with siblings, but the implied usage is clear enough.

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