discover_tables

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

With no annotations, the description carries the full burden. It discloses ~15s latency and output composition, which is useful. But it does not state whether the operation is read-only, any auth requirements, failure modes, or how the agent handles ambiguous questions, leaving notable gaps.

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?

Two focused sentences with no redundancy. It front-loads the core action and then adds concise, useful context about speed and output structure.

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?

The description gives a good overview for a discovery tool and leverages the existing output schema (so return values are covered). However, it lacks explanation of the knowledge_cluster_id parameter and any prerequisites, making it not fully self-sufficient for correct invocation.

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 description does not explicitly explain the parameters. 'Question' is implied by the context, but 'knowledge_cluster_id' is never mentioned, leaving a required parameter ambiguous. With zero schema documentation, the description fails to compensate.

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 asks the Data Discovery agent for relevant tables and columns, and specifies the output includes tables, join relationships, and a per-table column shortlist. It distinguishes itself as a fast starting point before writing SQL, differentiating it from other table or SQL 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?

It explicitly says 'the best starting point before writing SQL,' giving a clear when-to-use context. However, it does not mention alternatives or when not to use it, so it lacks full exclusion guidance.

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