agentbay_memory_recall

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

With no annotations, the description carries the full burden of behavioral disclosure. It explains the hybrid search algorithm (RRF fusion) and a performance optimization (skip vectors via fast=true). It implies a read-only search operation with no side effects, though it does not explicitly state idempotency or rate limits.

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 extremely concise, with three short sentences front-loading the purpose and key usage notes. Every sentence adds distinct value: the first states what the tool does, the second and third give actionable parameter guidance. There is no redundancy or extraneous information.

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?

The description covers the search method and two important parameters, but it lacks details on output format (e.g., what is returned, how results are structured). It does not explain the alias+tag+full-text+vector search modes further, nor the effect of the format parameter (json vs context). Given the complexity of hybrid search with RRF fusion, a bit more context on output would improve completeness.

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 78%, so many parameters already have descriptions. The description adds value by explaining how to use tokenBudget (control context size) and fast (skip vectors for speed), which goes beyond the schema definitions. These insights help the agent use the tool more effectively.

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?

Description clearly states 'Search project memory using hybrid search' with specific techniques (alias, tag, full-text, vector, RRF fusion). It identifies the resource (project memory) and action (search), distinguishing it from sibling tools like agentbay_memory_store which is for storing, and agentbay_knowledge_query which targets knowledge rather than project memory.

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?

Description provides two parameter usage tips: 'Use tokenBudget to control context size' and 'Use fast=true to skip vectors'. However, it does not explicitly state when to use this tool vs. alternatives like agentbay_knowledge_query or agentbay_agent_memory_query, nor does it mention prerequisites or contraindications.

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