Procore MCP Server

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

No annotations are provided, so the description carries the full burden. It mentions 'GET' (implying read-only) and lists parameters, but doesn't disclose behavioral traits like pagination behavior (page/per_page usage), rate limits, authentication requirements, error conditions, or response format. The description is minimal and lacks crucial operational context for a tool with 12 parameters.

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 concise with two sentences: one stating the purpose and category, another showing the endpoint. It's front-loaded with the core action. However, it could be more structured by explicitly separating purpose from technical details, and the category hint is somewhat cryptic.

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 complexity (12 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain the return format, pagination, error handling, or domain context ('Manpower Logs'). For a list operation with many filtering options, more guidance on usage and output is needed to be fully helpful to an AI agent.

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 100%, so parameters are well-documented in the schema. The description adds no parameter semantics beyond the schema—it doesn't explain interactions (e.g., log_date vs. start_date/end_date exclusivity) or provide examples. Baseline 3 is appropriate since the schema does the heavy lifting, but the description doesn't compensate with additional insights.

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 states the tool's purpose as 'List Manpower Logs' with a category hint '[Project Management/Daily Log]' and the HTTP endpoint. It specifies the verb 'List' and resource 'Manpower Logs', but doesn't differentiate from sibling tools (like 'list_manpower_logs_contact_options' or 'list_manpower_logs_vendor_options') or explain what 'Manpower Logs' are. The purpose is clear but lacks sibling distinction and domain context.

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 is provided. The description doesn't mention prerequisites, constraints, or compare it to sibling tools (e.g., filtered vs. unfiltered listing). Usage is implied by the endpoint and parameters, but explicit when/when-not instructions are absent.

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