prob_forecast

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

No annotations provided, so description carries full burden. It describes output (downsampled rate profiles, cumulative milestones) but does not explicitly state non-destructive nature, auth requirements, or side effects. Adequate but not exhaustive.

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?

Description is concise with purpose front-loaded. Includes both output details and argument descriptions. Minor improvement could be separating output description from args.

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 moderate complexity (6 params, output schema exists), description covers input semantics and output nature. Doesn't detail return format (acceptable due to output schema), but sufficiently explains what the tool produces.

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 has 0% description coverage, but description adds meaningful explanations for each parameter (e.g., 'qi_dist: Dict with mean and std'). Provides defaults for non-required params, adding value beyond schema. Explanation for distribution dicts is slightly vague but still helpful.

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?

Clearly states 'Generate P10/P50/P90 rate-time forecast profiles', specifying verb and resource. Explicitly distinguishes itself from sibling tool 'mc_eur' by noting it returns full rate-time curves not just EUR summaries.

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?

Provides direct comparison with sibling 'mc_eur', indicating when to use this tool (for full rate-time curves vs. EUR summaries). Implies context for probabilistic forecasting without explicit exclusions.

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