Procore MCP Server

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

No annotations are provided, so the description must fully disclose behavioral traits. It mentions the HTTP method (PATCH) and endpoint, implying a partial update, but fails to describe critical behaviors such as required permissions, whether the update is destructive, error handling, or response format. The description is insufficient for a mutation tool with no annotation support.

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 and front-loaded, stating the core purpose in the first sentence. The inclusion of the API endpoint adds technical context without unnecessary verbosity. However, the bracketed category '[Project Management/Field Productivity]' is somewhat redundant and could be omitted for better focus.

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 of a mutation tool with 20 parameters, no annotations, and no output schema, the description is inadequate. It lacks essential context such as expected return values, error conditions, authentication requirements, and operational constraints. The description does not compensate for the missing structured data, leaving significant gaps for 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?

The input schema has 100% description coverage, providing detailed documentation for all 20 parameters. The description adds no additional parameter semantics beyond what the schema already explains, such as clarifying dependencies or usage examples. With high schema coverage, the baseline score of 3 is appropriate.

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 action ('Edit') and resource ('a Timecard Entry'), making the purpose specific. It also includes the API endpoint, which reinforces the operation. However, it does not explicitly distinguish this tool from sibling tools like 'update_timecard_entry' or 'bulk_update_timecard_entries', which limits the score to 4.

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 lacks context about prerequisites (e.g., needing an existing timecard entry), exclusions, or comparisons to sibling tools like 'create_timecard_entry_v1_1' or 'bulk_update_timecard_entries'. This absence of usage instructions results in a low score.

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