petropt/petro-mcp

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

No annotations are provided, so the description carries full burden. It describes what the tool generates (rate-time curves, downsampled profiles, cumulative milestones) and mentions default values, but doesn't cover behavioral aspects like computational requirements, error conditions, or output format details beyond the high-level description.

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 a purpose statement, sibling comparison, output description, and parameter documentation. While comprehensive, it maintains efficiency with no wasted sentences. The parameter section could be slightly more concise but remains focused.

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 (probabilistic forecasting with 6 parameters including nested objects) and no annotations, the description does well by explaining purpose, differentiation, outputs, and all parameters. Since an output schema exists, the description doesn't need to detail return values. The main gap is lack of behavioral context like performance characteristics.

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 explaining all 6 parameters in detail. Each parameter gets a clear explanation of its purpose (e.g., 'Dict with mean and std for initial rate'), units where applicable ('months'), and default values. This adds substantial meaning 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 generates 'P10/P50/P90 rate-time forecast profiles' and distinguishes it from sibling 'mc_eur' by noting it returns 'full rate-time curves at each percentile' rather than just EUR summaries. This provides specific verb+resource differentiation.

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 explicitly states when to use this tool versus an alternative: 'Unlike mc_eur which returns only EUR summaries, this generates the full rate-time curves at each percentile.' This provides clear guidance on tool selection.

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