get_composite_site_score

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

Annotations already indicate readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the description does not need to restate safety. However, the description adds valuable behavioral context: 'never imputes a missing one', 'water is unavailable only outside basin coverage (never faked)', 'market/DCPI is v1-unavailable (use rank_markets)'. This goes beyond annotations, but the description could still mention the read-only nature more directly.

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 moderately long but well-structured: use-case statement, differentiation from siblings, example, return structure. It front-loads the essential purpose and usage. A minor improvement could be trimming redundant phrases, but overall it's efficient and informational.

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?

Without an output schema, the description carries the full burden of explaining the return value. It lists the return fields (composite_score, verdict, confidence, coverage, coverage_ratio, sub_scores, caveats) and explains the coverage map structure. It also covers edge cases (water uncovered outside basins) and scenarios for other tools. Given the tool's complexity, the description is remarkably complete.

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?

All three parameters (lat, lon, state) have descriptions in the input schema, so schema coverage is 100%, baseline 3. The description adds value with a concrete example (lat=33.45, lon=-112.07, state=AZ) and clarifies the role of state ('improves water/context lookups'). This provides practical usage context 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 clearly states the tool's purpose: providing a single 0-100 site suitability/risk verdict with a per-factor coverage map. It explicitly names the tool's unique behavior (scoring only over validated factors, never imputing missing ones) and differentiates from sibling tools like analyze_site, compare_sites, and rank_markets.

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 opens with 'Use when a user wants ONE honest 0-100 site suitability/risk verdict...' and explicitly contrasts with related tools: 'Unlike analyze_site...', and provides alternative tools for different needs (analyze_site for full data, compare_sites for 2-4 sites, rank_markets for whole-market ranking). This gives clear when-to-use and when-not-to-use guidance.

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