gitlab mcp

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

With no annotations provided, the description carries the full burden of behavioral disclosure. While 'Update' implies a mutation operation, it doesn't disclose critical behavioral traits such as required permissions, whether changes are reversible, error conditions (e.g., invalid label_id), or what happens to unspecified fields (partial vs. full updates). For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.

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 a single, efficient sentence that states the core purpose without any wasted words. It's appropriately sized for a tool with a clear function and well-documented schema. Every word earns its place by conveying essential information about the tool's action and target.

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 (mutation operation with 6 parameters) and the absence of both annotations and an output schema, the description is insufficiently complete. It doesn't explain what the tool returns, error handling, or behavioral nuances. While the schema covers parameters well, the description fails to compensate for the lack of annotations and output schema, leaving the agent with incomplete context for proper tool invocation.

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 schema description coverage is 100%, meaning all parameters are documented in the schema itself. The description adds no additional parameter semantics beyond what's already in the schema (e.g., it doesn't explain relationships between parameters or provide examples). According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.

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 ('Update') and target resource ('an existing label in a project'), which is specific and unambiguous. It distinguishes this from sibling tools like 'create_label' and 'delete_label' by specifying it updates existing labels rather than creating or deleting them. However, it doesn't explicitly mention what aspects of the label can be updated, which prevents a perfect score.

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 doesn't mention prerequisites (e.g., needing an existing label), when not to use it (e.g., for creating new labels), or how it differs from similar tools like 'update_issue' or 'update_merge_request'. The agent must infer usage from the tool name and schema alone.

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