detect_environment_trends

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

With no annotations provided, the description carries the full burden. It clearly explains the return format (JSON with slope, direction, projection, alert flag) and notes the API limitation of ~1257 records per day, which affects data density. This is sufficient transparency for a read-only analysis tool.

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 well-structured with Args and Returns sections, and the API limitation note is useful. It is fairly concise, though the note could be integrated more succinctly. Still, it avoids redundancy and is easy to parse.

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 low complexity (2 parameters, no nested objects) and that an output schema exists, the description covers purpose, parameters, return structure, and a key limitation. It is fully informative for an AI agent to select and invoke the tool 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?

The input schema has 0% description coverage, but the description fully compensates by explaining device_id as 'The AC Infinity device code (from discover_devices)' and days with default, range (1–30). This adds crucial meaning beyond the schema's basic type info.

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 explicitly states it detects linear trends in temperature, humidity, and VPD over a look-back window. The verb 'detect' and the resource 'environment trends' are specific and distinct from sibling tools like check_vpd_drift (focuses on drift) and get_historical_readings (raw 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 implies usage for trend analysis but does not explicitly state when to use this tool versus alternatives like check_vpd_drift or get_environment_health. The note about API data sparsity provides some context, but explicit when-to-use and when-not-to-use guidance is missing.

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