cortex-mcp

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It states the tool retrieves a 'full report' but doesn't specify what that includes (e.g., analysis results, logs, artifacts), whether it's a read-only operation, potential errors (e.g., if job isn't completed), or performance considerations. The description is minimal and lacks essential behavioral context for a tool that likely returns complex data.

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 directly states the tool's function without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse. Every part of the sentence contributes to understanding the purpose, with zero waste.

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 lack of annotations and output schema, the description is insufficient for a tool that likely returns detailed analysis results. It doesn't explain what a 'full report' entails, how it differs from other job-related tools, or any behavioral nuances. For a tool in a complex domain (analysis jobs) with rich siblings, more context is needed to guide effective use.

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 the single parameter 'jobId' clearly documented. The description doesn't add any parameter-specific details beyond what the schema provides (e.g., format examples or constraints). Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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 ('Get') and resource ('full report of a completed analysis job'), making the purpose immediately understandable. It doesn't explicitly differentiate from siblings like 'cortex_get_job' or 'cortex_wait_and_get_report', but the focus on 'full report' provides some distinction. The description avoids tautology by specifying what is being retrieved rather than just restating the tool name.

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., that the job must be completed), nor does it compare with siblings like 'cortex_get_job' (which might return summary info) or 'cortex_wait_and_get_report' (which might handle waiting). Without such context, an agent must infer usage from tool names alone.

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