memory_enhanced_recommendation

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

No annotations are provided, so the description should disclose behavioral traits. It mentions 'using learning' but does not clarify if this tool modifies state (e.g., learns from recommendations) or is read-only. The term 'get' suggests read-only, but 'learning' implies potential side effects.

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 concise sentence (9 words). However, conciseness comes at the cost of missing critical details. The structure is adequate but not informative.

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 three required parameters (including two empty objects), no output schema, and a complex domain (learning and knowledge graph), the description is severely incomplete. It does not explain the return value, prerequisites, or how the enhancement works, leaving the agent unable to use the tool effectively.

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 67% description coverage (projectPath and baseRecommendation described, projectFeatures missing). The description does not add any parameter semantics beyond the schema. It fails to clarify what 'projectFeatures' should contain or how parameters interact.

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 states the tool gets enhanced recommendations using learning and knowledge graph, but it is vague. It does not specify what 'enhanced' means or differentiate from sibling tools like memory_knowledge_graph or memory_recall that also use knowledge graphs.

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?

No guidance on when to use this tool versus alternatives. The description lacks any context about prerequisites, such as whether memory must be populated first, or scenarios where this tool is preferred over other memory tools.

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