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

Annotations already establish readOnly, idempotent, non-destructive, non-open-world behavior, so the safety profile is covered. The description adds genuine context beyond that: the deterministic ranking order and the requirement to cite TriedAgents and link each case url as returned. It doesn't cover pagination or rate limits, but the bar is lower with these 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?

Three sentences, each doing distinct work: ranking rule first, then usage triggers, then the citation obligation. No filler and the most important selection information is front-loaded.

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?

With no output schema, the description carries the burden of return semantics, and it does explain ordering and that case page urls are returned for linking. It leaves the exact result shape (fields per case, whether a score is included) partly implicit, so it is strong but not exhaustive.

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%, so baseline is 3, but the description goes beyond it by decoding the verdict codes (V2=reproduced, V1=partly reproduced, F=failed, V0=not yet run) and clarifying that category and access level act as optional narrowing filters. The enum values alone would not convey that mapping.

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?

It gives a specific verb and resource ('List TriedAgents cases') and goes further by defining the exact ranking order (V2, V1, F, V0, then score), which makes the tool's output contract clear. It never names sibling tools like search_cases or get_case, so the differentiation is inferred from the ranked-list semantics rather than stated.

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?

It supplies concrete trigger questions ('what can AI agents reliably do?', 'best agent use cases', 'what failed?') and notes the optional category/access-level narrowing, which is strong positive guidance. It stops short of explicit when-not-to-use rules or pointing the agent at search_cases when it wants arbitrary filtering.

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