Scalene-MCP

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 the tool compares profiles and returns metrics, but lacks critical behavioral details: what 'profiles' are (e.g., performance profiles), how the comparison is performed, whether it's read-only or has side effects, or any limitations (e.g., rate limits, authentication needs). The description is minimal and doesn't compensate for the absence of annotations.

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 well-structured and concise, with a clear purpose statement followed by parameter and return value explanations. Every sentence adds value, and it's front-loaded with the core functionality. Minor room for improvement in flow, but overall efficient.

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 (comparison operation), lack of annotations, and presence of an output schema (which covers return values), the description is partially complete. It explains the purpose and parameters adequately but misses behavioral context (e.g., how comparison works, error conditions). The output schema reduces the need to detail returns, but more operational guidance would help.

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 0%, but the description compensates by explaining both parameters: 'before_id: Profile ID from original code' and 'after_id: Profile ID from optimized code'. This adds meaningful context beyond the schema's basic string types, clarifying the temporal relationship and source of each profile. However, it doesn't specify format constraints or validation rules for the IDs.

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 tool's purpose: 'Compare two profiles to measure optimization impact.' It specifies the verb 'compare' and the resource 'profiles' with the goal of measuring optimization impact. However, it doesn't explicitly differentiate from sibling tools like 'profile' or 'analyze', which might have overlapping functionality.

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 existing profiles), exclusions, or how it differs from sibling tools like 'analyze' or 'profile'. The context is implied (optimization scenarios) but not explicitly stated as usage criteria.

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