@git-fabric/aiana

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that it 'Returns memories ranked by relevance' but does not cover aspects like rate limits, authentication needs, error handling, or what constitutes a 'memory' in this context. This is insufficient for a search tool with potential operational constraints.

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 two clear sentences that directly state the tool's function and output. There is no wasted language, and it efficiently communicates the core purpose without unnecessary elaboration.

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 of a semantic search tool with no annotations and no output schema, the description is incomplete. It does not explain the format of returned memories, how relevance is calculated, or any limitations (e.g., search scope or performance). This leaves significant gaps for an AI agent to understand the tool's behavior fully.

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 input schema fully documents all parameters. The description does not add any additional meaning beyond what the schema provides, such as explaining the semantic nature of the search or how the 'minScore' threshold affects results. Baseline 3 is appropriate as the schema handles parameter documentation.

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 as 'Semantic search over stored memories' with the action 'Returns memories ranked by relevance to the query.' It specifies the verb (search) and resource (memories) but does not explicitly differentiate from siblings like aiana_memory_recall, which might have overlapping functionality.

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 such as aiana_memory_recall or other sibling tools. It lacks context on specific use cases, exclusions, or prerequisites, leaving the agent to infer usage based on the name alone.

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