scale_services

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. 'Scale services up or down' implies a mutation operation, but the description doesn't disclose critical traits: whether this is destructive (e.g., terminates instances), requires specific permissions, has rate limits, or what the expected outcome is (e.g., returns a job ID or status). The mention of 'resource analysis' hints at a basis but doesn't clarify if it's automated or manual input. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

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 purpose without redundancy. It's front-loaded with the core action ('scale services up or down') and avoids unnecessary words. Every part of the sentence contributes meaning, making it highly concise and well-structured for quick comprehension.

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 (mutation tool with nested parameters, no output schema, and no annotations), the description is incomplete. It doesn't address behavioral aspects like safety (e.g., use 'validate_only' for dry runs), response format, error handling, or dependencies on other tools (e.g., needing service info first). For a tool that modifies infrastructure, this lack of context could lead to misuse or confusion by an 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?

Schema description coverage is 100%, so the schema already documents both parameters ('scaling_plan' and 'validate_only') with details like nested objects for 'scale_up' and 'scale_down'. The description adds no parameter-specific semantics beyond implying that scaling is 'based on resource analysis', which loosely relates to the 'scaling_plan' parameter but doesn't explain its structure or usage. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't significantly enhance parameter understanding.

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 ('scale services up or down') and the basis ('based on resource analysis'), providing a specific verb and resource. It distinguishes the tool's purpose from many siblings like 'get_service_status' or 'install_service' by focusing on scaling operations. However, it doesn't explicitly differentiate from potential scaling-related siblings like 'deploy_vm' or 'control_vm', which might involve similar concepts.

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 mentions 'based on resource analysis' but doesn't specify what triggers scaling, prerequisites (e.g., needing prior analysis from tools like 'analyze_network_topology'), or exclusions (e.g., not for initial deployments). With many sibling tools for infrastructure management, this lack of context leaves the agent guessing about appropriate usage scenarios.

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