@git-fabric/aiana

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

No annotations are provided, so the description carries the full burden. It discloses the return data (stats like memory count and model), which is useful behavioral context. However, it lacks details on permissions, rate limits, error handling, or whether it's a read-only operation (implied by 'Return' but not explicit). For a tool with zero annotation coverage, this leaves significant gaps in behavioral understanding.

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, efficient sentence that front-loads the purpose ('Return collection stats') and lists key metrics. Every word earns its place, with no redundancy or fluff. It's appropriately sized for a simple, parameterless tool.

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 (simple, no parameters) and lack of annotations/output schema, the description is minimally complete. It explains what stats are returned, which is sufficient for basic use. However, it doesn't cover behavioral aspects like error cases or performance, leaving room for improvement despite the low complexity.

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?

The tool has 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description doesn't add param info, which is appropriate. Baseline for 0 params is 4, as it correctly avoids unnecessary details and aligns with 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 tool's purpose with a specific verb ('Return') and resource ('collection stats'), listing the specific metrics returned. It distinguishes from siblings like aiana_health (likely system health) and aiana_memory_search (searching memories), though not explicitly. However, it doesn't fully differentiate from aiana_session_list, which might also return stats-like data.

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?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, timing, or comparisons to siblings like aiana_health (which might overlap for health stats) or aiana_memory_search (which might provide filtered data). Usage is implied only by the purpose, with no explicit when/when-not instructions.

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