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

With no annotations, the description carries the full burden. It discloses the DuckDB engine, locked file/network access, cost of 1 credit per call, and automatic refund on failure. These are meaningful behavioral traits beyond basic functionality. It does not mention all potential side effects, but for a join operation, the disclosure is strong.

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 two sentences, densely packed with purpose, return type, cost, differentiator, engine, security restrictions, and refund policy. It is front-loaded and every sentence carries meaningful information. No filler or repetition.

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 10 parameters and no output schema, the description offers substantial context: engine, security locks, cost, refund guarantees, and the unique value proposition. It is thorough for practical use, though it could be more explicit about the need to supply two file sources (file_id vs base64), but this is covered by the schema.

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 input schema covers all parameters with descriptions (coverage 100%), including 'on', 'how', format overrides, limit, columns, and file inputs. The description does not add additional parameter-level semantics beyond what the schema already provides, so the baseline of 3 is appropriate.

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 function: joining two data files on common columns, with an illustrative example (orders × customers). It also specifies the output as actual data rows in JSON. It distinguishes itself from sibling tool data_query by noting that cross-file alignment is not possible there, which aids selection.

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 indicates when to use this tool: for cross-file joins that data_query cannot handle. It names the alternative and provides context, though it does not cover all sibling tools or negative cases (e.g., when not to use). This is clear but not exhaustive.

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