recall

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

With no annotations provided, the description fully discloses behavior: it returns key clusters with specific fields (canonical concept, aliases, etc.), not memory content. It details injection behavior, defaults, truncation, and parameter effects (inject_prefer_depth, inject_explore_shallow, inject_min_rel_score). No contradictions exist.

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 dense with information and front-loaded with the core purpose. It could be structured more cleanly (e.g., bullet points for parameters) but is not overly verbose. Every sentence adds value, though some details could be consolidated.

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 no output schema and 9 parameters, the description covers return structure (keys vs. memories), injection behavior, truncation, and workflow. Missing details on 'top_k' and 'namespace', plus no error handling or rate limits, but the core functionality is well-explained.

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 0%, but the description explains most parameters: query (short focused nouns), inject, inject_top_k, inject_max_chars, inject_min_rel_score, inject_prefer_depth, inject_explore_shallow. However, 'top_k' and 'namespace' are not described, leaving gaps. Overall, it adds substantial meaning beyond the schema.

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 verb ('Search') and the resource ('long-term memory'), and specifies the context: 'what is already known about the user, project, or topic'. It distinguishes the tool by its search-and-retrieval purpose, contrasting with siblings like 'remember_batch' (write) or 'list_memories' (list).

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?

Explicit guidance is given: 'call this before your first reply and whenever the topic shifts', 'Use short focused noun queries', and 'decompose multi-fact questions into several recall calls'. It also instructs to follow up with read_key() and read_memory() for full content, and explains when to use injection as an alternative.

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