Enhanced Knowledge Graph Memory Server

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. It mentions the tool 'fuses multiple relevance signals' and offers 'better recall,' but lacks details on performance characteristics (e.g., speed, cost), error handling, or output format. For a search tool with no annotations, this leaves significant gaps in understanding its behavior.

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 highly concise and front-loaded, consisting of just two sentences that directly convey the core functionality and benefit. Every word earns its place, with no redundant or vague phrasing.

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 (4 parameters with nested objects, no output schema, and no annotations), the description is insufficient. It doesn't explain the return values, result ordering, pagination, or how the hybrid approach affects performance. For a sophisticated search tool, more context is needed to guide effective use.

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 all parameters thoroughly. The description doesn't add any meaningful semantic context beyond what's in the schema (e.g., it doesn't explain how the 'combined signals' interact with parameters like 'weights' or 'filters'). Baseline score of 3 is appropriate as the schema does the heavy lifting.

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: 'Search using combined semantic, lexical, and metadata signals.' It specifies the verb ('search') and the approach ('combined signals'), but doesn't explicitly differentiate from sibling search tools like 'semantic_search', 'boolean_search', or 'fuzzy_search' beyond mentioning 'better recall than single-signal search.'

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 implies when to use this tool ('Provides better recall than single-signal search'), suggesting it's preferable for comprehensive searches. However, it doesn't explicitly state when to choose it over alternatives like 'semantic_search' or 'boolean_search', nor does it provide exclusions or prerequisites for usage.

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