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 of behavioral disclosure. It states 'Delete', which implies a destructive mutation, but does not clarify if the deletion is permanent, reversible, or requires special permissions. The API endpoint hint suggests a REST DELETE operation, but the description lacks critical details like side effects, error conditions, or confirmation requirements for a destructive action.

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 extremely concise—just two brief phrases and an API endpoint. It is front-loaded with the core action ('Delete Productivity Log') and wastes no words. However, it is arguably too terse, omitting necessary context that would help an agent use the tool effectively, which slightly detracts from its utility despite efficient wording.

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 destructive nature, lack of annotations, and absence of an output schema, the description is incomplete. It fails to address key contextual aspects: what a 'Productivity Log' is, the consequences of deletion, required permissions, or what the tool returns (e.g., success confirmation or error). For a mutation tool with zero annotation coverage, this leaves 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, with clear parameter definitions ('Unique identifier for the project' and 'Productivity Log ID'). The description adds no additional parameter semantics beyond what the schema provides. Since schema coverage is high, the baseline score of 3 is appropriate—the description neither compensates for gaps nor adds value beyond the structured 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 'Delete Productivity Log' is a tautology that merely restates the tool name without adding specificity. It includes a category tag '[Project Management/Daily Log]' and an API endpoint, but does not clearly articulate what the tool does beyond the obvious verb 'Delete'. It lacks differentiation from sibling tools (e.g., other delete operations like delete_delay_log, delete_notes_log).

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 does not mention prerequisites (e.g., needing a specific project ID and log ID), nor does it indicate when deletion is appropriate (e.g., for correcting errors, removing obsolete entries). With no usage context, the agent must infer everything from the tool name and parameters alone.

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