explain

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

With no annotations available, the description carries the full burden. It accurately discloses the core behavior—walking proof trees, producing natural-language steps, and citing rule IDs when present. It does not contradict any annotations (there are none). Missing details include side effects (likely none, but unstated) and behavior when there are no solutions, but the description gives a strong sense of what happens internally.

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 two sentences, front-loaded with the verb and purpose, and every phrase adds value. There is no redundancy or fluff.

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 there are 6 parameters, no annotations, and an output schema exists, the description is adequate for understanding the tool's primary purpose and output, but incomplete regarding parameter roles and usage context (e.g., how kb_id relates to knowledge, when to vary max_depth vs. max_solutions). The output schema covers return values, so that is not a gap, but the parameter and selection guidance are thin.

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 for parameter meaning. It adds context for 'query', implicitly for 'max_depth' and 'max_solutions' via 'walk the proof tree of each solution', but leaves 'kb_id', 'knowledge', and especially 'delta_knowledge' undefined. The description does not explain the relationship between these parameters or how they affect the explanation.

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 uses a specific verb ('Explain'), names the resource ('how a query is proven'), and specifies the method and output ('walk the proof tree of each solution and return readable reasoning steps'). It clearly distinguishes this from siblings like 'reason' (likely performs reasoning) and 'diagnose' (likely investigates problems) by focusing on natural-language explanation of proofs.

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 clearly implies the use case: when a user needs a human-readable explanation or proof trace for a query. However, it does not explicitly name alternatives or state when not to use this tool (e.g., when one actually wants to run a query vs. understand its derivation).

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