get_memory_health

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

With no annotations, the description carries the burden of disclosing behavior. It explains the effect of fix_indexes (rebuilding indexes), indicating a potentially destructive action. However, it does not mention other aspects like return format or permissions, though the output schema likely covers that.

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 exceptionally concise, with two sentences for purpose and one for parameter details. Information is front-loaded and every word adds value, making it efficient for an AI agent to parse.

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 simple single-boolean-parameter tool and presence of an output schema, the description is complete. It explains purpose, reports, and parameter behavior, adequately covering the agent's needs.

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 parameter fix_indexes has no schema description (0% coverage), but the description adds clear semantic meaning: 'If true, rebuild all MEMORY.md indexes from actual files on disk.' This goes beyond the schema's type and default, telling the agent exactly what invoking the parameter does.

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 analyzes saved memory health across all projects and sessions, listing specific outputs like duplicates, stale memories, index integrity, and suggestions. This distinguishes it from sibling tools such as list_shared_memories or search_memories, which focus on listing or searching rather than analysis.

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 does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention prerequisites or when not to use it. The purpose is implied but lacks direct instructions for an AI agent.

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