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 states the tool 'calculates' pressures, implying a read-only computation, but does not disclose behavioral traits such as error handling, unit assumptions, or output format. For a calculation tool with no annotations, this lacks necessary context about reliability or limitations.

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 efficiently structured: a purpose statement, formulas, and parameter definitions in a bullet-like format. Every sentence adds value without redundancy, making it easy to parse and front-loaded with critical information. It avoids unnecessary elaboration while covering key details.

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 (formula-based calculation with 4 parameters), no annotations, and an output schema (implied by context signals), the description is mostly complete. It explains the purpose, formulas, and parameters well, but lacks behavioral context (e.g., error cases). The output schema likely covers return values, so the description's focus on inputs is appropriate, though some operational guidance would enhance completeness.

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 description coverage is 0%, so the description must fully compensate. It explicitly lists all four parameters with clear definitions (e.g., 'sidp_psi: Shut-in drill pipe pressure (psi)'), including units and abbreviations. This adds essential meaning beyond the schema's generic titles, ensuring the agent understands each input's role in the formulas.

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 specific purpose: 'Calculate Initial and Final Circulating Pressures for well kill operations.' It includes the exact formulas (ICP = SIDP + slow circulating pressure; FCP = SCP * (Kill MW / Original MW)), which precisely defines what the tool computes and distinguishes it from sibling tools focused on other petroleum engineering calculations like annular velocity, economics, or pressure gradients.

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. While it mentions 'well kill operations,' it does not specify prerequisites, conditions, or compare it to related sibling tools (e.g., calculate_kill_mud_weight). This leaves the agent without context for tool selection in complex workflows.

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