get_optimization_plan

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

With no annotations, the description carries full burden. It discloses the return structure '{specs_total, *_count, *[], markdown}', explains layers and how toggles work, and implies a read-only nature. It does not mention destructive traits or auth needs, which is acceptable for a reporting tool.

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 dense paragraph but front-loads the key purpose. Every sentence adds value, though it could be more scannable with bullet points. It is appropriately sized for the complexity.

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 (3 layers, 4 params, no output schema), the description covers the output structure and layer behavior. It does not detail the markdown format, but that is acceptable. The tool is well-placed among siblings that handle individual signals.

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 coverage is 0%, but the description fully compensates by explaining each parameter: include_coverage/quality/drift booleans (default true) toggle layers, top_n integer (default 10) caps rows. It adds context beyond the schema types, making parameter usage clear.

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 it provides a 'Three-layer coach output' that integrates coverage/quality/drift signals into a prioritized markdown plan, with specific use cases like 'what should we fix next'. This distinguishes it from sibling tools that focus on individual signals (e.g., get_coverage_matrix, get_drift_report).

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?

It explicitly gives usage scenarios: 'when a user asks what should we fix next / show me the weekly plan / review the suite'. It also explains how to toggle layers via booleans. However, it does not mention when not to use or provide alternatives (e.g., for individual signals).

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