printer_trend_analysis

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

No annotations are provided, so the description carries the full burden. It states data stays local (privacy) and lists return types, but does not disclose prerequisites (e.g., printer existence), side effects, or error handling. It is not contradictory but lacks depth.

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 concise with a single sentence for purpose, a privacy note, and a bulleted list of outputs, followed by parameter explanations. Every sentence adds value, and it is front-loaded with the main purpose.

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?

For a simple tool with 2 parameters and no output schema, the description covers the core functionality, privacy, and output types. It does not explain error cases or return format, but given the tool's simplicity, it is reasonably complete.

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 the description must compensate. It explains printer_name as the printer to analyze and lookback_days as how far back to look with a default of 30 days, adding valuable meaning beyond the schema's title and type.

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 analyzes local print history trends for a specific printer, listing specific outputs like health score and failure rate trends. It distinguishes itself from siblings by focusing on trends over time and local data.

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 mentions it uses local database data only, implying it's for local analysis, but does not explicitly state when to use this tool versus alternatives like analyze_print_failure or predict_print_failure. No exclusion criteria or use cases are given.

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