analyze_trends

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

With no annotations, the description carries the full burden. It states the tool analyzes and computes, implying a read-only operation, but does not explicitly confirm non-destructiveness or file permissions. The output schema is not described, but since it exists, the description suffices for basic transparency.

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 very concise: two sentences covering purpose and outputs, followed by a clean Args list. No redundant or vague statements. Every sentence earns its place.

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 complexity and the presence of an output schema, the description is largely complete. It explains the inputs, the operations (trend computation and anomaly detection), and lists key outputs. Minor gaps: no mention of expected CSV format (e.g., required columns) or anomaly flag details, but these are mitigated by the output 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 description adds meaning beyond the input schema: it specifies that file_path must be an absolute path to a CSV file, and well_name is an optional filter. Since schema description coverage is 0%, this additional context significantly aids correct usage.

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 analyzes production trends and detects specific anomalies (shut-ins, rate jumps, water breakthrough, GOR blowouts). It lists computed outputs (water cut, GOR, decline rate, cumulative production) which distinguishes it from siblings like fit_decline or rta_* that focus on curve fitting or reservoir analysis.

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?

No guidance on when to use this tool versus alternatives. The description does not mention prerequisites, when-not-to-use, or explicitly compare with sibling tools like query_production or decline fitting tools. The implied usage is for trend analysis, but an agent would not know when to prefer this over others.

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