resource_bottleneck_forecaster

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

With no annotations provided, the description carries the full burden. It mentions the analysis method ('time-series analysis') and output structure, but lacks details on permissions needed, rate limits, whether it's read-only or mutative, execution time, or error conditions. The behavioral disclosure is incomplete for a forecasting 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 and appropriately sized. It begins with a clear purpose statement, explains the methodology, provides detailed parameter documentation, and specifies the return structure. Every sentence adds value with no redundancy or fluff.

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 (7 parameters, forecasting functionality) and the presence of an output schema, the description is mostly complete. It explains parameters thoroughly and mentions the return structure. However, without annotations and given the forecasting nature, it could benefit from more behavioral context about reliability, data sources, or limitations.

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?

With 0% schema description coverage, the description fully compensates by providing detailed parameter explanations. Each of the 7 parameters is clearly documented with meaning, allowed values, and defaults (e.g., 'forecast_horizon: Forecast window - "1h", "6h", "24h", "7d", "30d" (default: "24h")'). This adds substantial value beyond the bare schema.

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 purpose with specific verbs ('forecast', 'analyze', 'predict') and resources ('resource bottlenecks', 'CPU, memory, disk, and network capacity constraints'). It distinguishes itself from siblings like 'check_resource_constraints' by focusing on forecasting rather than current state checking.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, appropriate contexts, or compare with sibling tools like 'check_resource_constraints' or 'predictive_log_analyzer', leaving the agent to guess based on tool names alone.

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