recall

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

With no annotations, the description carries the burden. It discloses result scoping ('limited to the memory scopes this client is allowed to see'), explains semantic_weight behavior (0.0-1.0 tuning, default -1), and implies read-only behavior for a search. No annotation contradiction.

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 paragraph that front-loads purpose and usage, then systematically explains parameters. Every sentence adds value, no fluff or repetition. It is efficiently structured for quick agent understanding.

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 an output schema exists (not shown), the description need not cover return values. It covers input parameters, behavior (scoping, hybrid search), and defaults. Could be more complete by mentioning result ordering or pagination, but overall sufficient for a search tool.

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 0%, but the description adds meaning for source, type, and semantic_weight (e.g., 'filters to one AI', 'tunes hybrid search'). It does not explain the limit parameter, which appears only in schema with default 8. Still, most parameters benefit from the description.

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 searches the user's unified memory across all AIs, and specifies use at task start to recover context. It distinguishes from sibling tools like recall_project by implying it covers all AIs, and explains filtering by source and type.

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 explicitly advises using this at the start of a task to recover context, and explains parameter usage (source, type, semantic_weight). It does not explicitly mention when not to use or alternative tools, but the context is clear given sibling tool names.

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