rank_imaging_priority

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

The annotation destructiveHint=true directly contradicts the description's claim that the tool is 'Deterministic — no LLM, no per-event cost' and only returns ranking data. The description gives no indication of any destructive side effect, and its entire framing suggests a read-only query. This is a critical inconsistency that could lead an agent to misuse the tool.

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 relatively long (5 sentences) but each sentence carries useful information: purpose, method, output, use case, and cost. It is front-loaded with the key question and efficient in its wording. A small deduction for density — the resolution-class explanation could be slightly tighter.

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?

For a tool with a rich output schema and fully documented input parameters, the description covers the essential context: what it returns, how to think about the output, determinism, and cost. It lacks nothing critical, though the annotation contradiction undermines trust. The tool's complexity is well-served by the description.

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?

The input schema covers 100% of parameters with descriptions, so the baseline is 3. The tool description adds minimal parameter-specific nuance — it only mentions resolution classes indirectly, but doesn't explain how bbox, top_n, or min_geoint_score interact with the ranking logic. Thus it neither adds nor subtracts much beyond the schema.

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 opens with a clear, specific question ('WHERE — and with what class of satellite — is observation most worthwhile right now?') and explains exactly what the tool does: ranks events by importance and resolution class. It clearly distinguishes from sibling tools like search_imagery and plan_event_imagery by framing itself as a triage step before imagery spending.

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 explicitly states the intended use case ('Use it to triage a theatre before spending on imagery') and explains the practical difference between resolution classes (hr = free Sentinel data, vhr = paid order). It doesn't name alternative tools or list exclusions, but the context is clear enough for an agent to decide when to invoke it.

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