Brain Recall

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

The annotations already indicate readOnlyHint=true and openWorldHint=false, so the base behavior is transparent. The description adds useful behavioral context beyond that: it explains that the tool returns ranked validators based on cross-engagement experience and that empty results signal no prior knowledge. This enriches the agent's understanding of what to expect, aligning with the lower bar set by the annotations.

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 concise (two sentences) and well-structured, front-loading the purpose and then providing usage guidance and fallback behavior. Every sentence adds value, with no redundant or filler content. The format is easy to parse and directly actionable.

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 that an output schema exists, the description does not need to detail return values. It adequately covers when to use the tool, what it provides, and how to interpret empty results. It also distinguishes itself from the technique index. The context is sufficient for an agent to decide whether to invoke this tool, though a bit more specificity about the ranking criteria could push it to a perfect score.

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%, so the description must compensate. It does reference the key parameters implicitly: 'vulnerability class' maps to vuln_class, 'technology stack' to technologies, and 'WAF' to waf_vendors. However, it does not explicitly explain the 'limit' parameter or provide detailed semantics for each field. The parameter names are self-explanatory, but coverage is incomplete, warranting a mid-range score.

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 explicitly states the tool's purpose: recalling what the 'neuron brain' has learned about testing, specifically which validators/techniques were effective for a given vulnerability class, technology stack, and WAF. It uses a clear verb ('recall') and identifies the resource (brain knowledge) and the output (ranked techniques). It also distinguishes itself from the static index, making its role unambiguous.

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 provides explicit guidance on when to use the tool: 'Consult before choosing validators or designing a test plan.' It also indicates when not to use it by stating 'Empty results mean no prior experience on this shape; proceed from the technique index,' which contrasts with alternative sources. This gives clear decision criteria for an agent.

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