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

The description adds significant behavioral context beyond annotations: it reduces context from 40000 to 800 tokens, returns matching tool names and parameter hints, and explicitly states it is read-only and has no side effects. Annotations already indicate readOnlyHint and idempotentHint, but the description enriches understanding of operational impact.

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 efficiently structured: it starts with the tool's core purpose, then states safety (read-only), then usage instructions, parameter details, and finally constraints and fallback actions. Every sentence contributes unique information with no redundancy.

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's meta-purpose and the presence of an output schema, the description covers all necessary aspects: what it returns, how it reduces context, when to use it, restrictions on recursion/validation, and a clear path for failure cases. It leaves no ambiguity for the agent to invoke it 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?

Schema description coverage is 100% for both parameters. The description provides added value by restating the query parameter with concrete examples like 'check if a Python package has CVEs' and clarifying the domain parameter's optional nature and allowed values. This goes beyond the schema's minimal descriptions, aiding the agent in formulating queries.

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: finding the right DataNexus tool by describing a task in plain English. It distinctly positions itself as a meta-tool for tool discovery, differentiating it from its many sibling tools that perform specific domain tasks.

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 gives explicit when-to-use guidance: 'Call this before any other DataNexus tool to reduce context load.' It also specifies when not to use it: 'Do not call this recursively or to validate results — use validate_tool_output for that.' Additionally, it provides a fallback mechanism for unexpected results via report_feedback.

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