akai_flash_qla

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

No annotations exist, and the description only states the functional category without disclosing behavioral traits such as destructive potential, resource requirements, or side effects. For a kernel tool, performance impact or data mutability is unknown.

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 very short (one line), which is concise but lacks structure. It front-loads the name and category but omits critical usage details.

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 (a kernel with CLi args), the description fails to explain expected inputs, output format, or behavior. No output schema is provided, and the description does not compensate for the lack of structured detail.

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 100% with generic parameters 'args' and 'stdin'. The description adds no additional meaning beyond the schema, so baseline score is appropriate.

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 identifies it as 'AkaiGDN Chunked Prefill (native C kernel)' under inference, which specifies a clear operation (chunked prefill) and distinguishes it from sibling tools with different kernels or purposes. The verb is implied but the resource is clear.

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 usage guidelines are provided. There is no indication of when to use this tool versus other inference-related siblings like 'akai_fpq' or 'akai_quant', nor any mention of prerequisites or exclusions.

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