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

Annotations already establish readOnly and idempotent behavior, and the description adds substantial non-obvious behavioral context: boards are dated, ordered oldest first, and the same risk is rephrased daily so matching must be semantic. It also discloses the size/depth tradeoff between detail levels and quantifies a 90-day pull at 'counts' as roughly a third the size. This goes well beyond 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 dense but well organized: core behavior first, then usage intent and interpretation caveat, then parameter specifics. Every sentence adds necessary information, and there is no padding or redundancy. The length is justified by the tool's multi-board, multi-level detail complexity.

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, the description covers the essential workflow: what is returned, ordering, how to interpret repeated risks, and how detail affects output size. The output schema exists, so return-value documentation is not the description's burden. The remaining gap is that scope and market parameters are not explained, which slightly reduces completeness for an agent deciding how to invoke the tool.

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 explain days_back range and default, and details the allowed values and meaning of detail ('counts', 'titles', 'full'). However, scope and market are left entirely undocumented, with only their defaults hinting at meaning. The compensation is strong for two parameters but incomplete overall.

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 explains that this tool returns all risk radar boards published over recent weeks, dated and sorted oldest first for trend analysis. It distinguishes itself from the sibling get_risk_radar by its temporal aggregation: instead of a single snapshot, it gives the full evolution of risks, regimes, and metrics. The specific use case of identifying new, carried, and dropped risks is explicit.

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 states when to use the tool: 'Use this to see which risks are new, which have been carried for weeks, which dropped off, and how their trend, impact and probability moved.' It also gives practical guidance to read boards in order and group risks by meaning. It does not explicitly name a more appropriate sibling for a single snapshot, so it lacks an explicit exclusion, but the intended context is clear.

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