sw_calibrate

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

Despite having no annotations, the description goes beyond basic operation by disclosing that the tool only produces data and does not make judgments, and that it will explain why items are inapplicable (e.g., CDL fixed CDF). It also provides specific 3GPP reference documents, making behavior highly predictable and well-documented.

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 front-loaded with the core purpose, then uses a bulleted list to efficiently enumerate outputs with standard clause references. It also adds a clear behavioral caveat about division of labor with sw_gate. Every sentence and bullet adds value; there is no fluff or 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?

The description covers the methodology, specific outputs with standard references, reference curve sources, what the tool does not do (no judgment), and how it handles inapplicable cases. Given there is also an output schema, the description is complete for an AI agent to select and invoke this tool correctly without needing further information.

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 only parameter, dataset_id, is not explicitly explained in the description, and schema coverage is 0%. However, the name is self-explanatory and the description implies the tool operates on a dataset by listing calibration outputs for a dataset. The description does not add extra meaning beyond the schema, but the intent is clear enough.

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 computes calibration quantities per 3GPP TR 38.901 §7.8, which is a specific and unambiguous verb+resource pairing. It also distinguishes itself from siblings by explicitly stating '本工具只出数不判决' (this tool only outputs numbers, not judgments) and pointing to sw_gate for the decision role.

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 positions the tool as the standard method for judging whether channel generation is correct, giving clear context for when it is appropriate. It explicitly excludes the judgment step by naming sw_gate as the tool that does that, and also notes that inapplicable cases will be explained, which helps the agent decide when this tool is relevant.

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