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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds valuable behavioral context: cache duration ('Cache 7j'), SLA ('SLA ≤20s'), keyless access ('keyless'), and the async execution option. No contradiction with 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 a dense but well-structured paragraph that front-loads the main purpose and follows with scenario, horizon, metric, output, source, and usage details. It avoids filler and each clause adds distinct information, though the length could be slightly reduced without losing value.

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 (6 parameters, output schema present), the description covers all essential aspects: purpose, scenarios, metrics, outputs, data sources, use cases, performance expectations, and auxiliary parameters like async. The output schema handles return-value details, so the description is 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?

Schema has 100% coverage, so baseline is 3. The description goes beyond the schema by elaborating on the meaning of metric values (e.g., 'température (delta vs baseline 1990-2010, jours >35°C, nuits chaudes)') and scenario options, enriching the parameter understanding.

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 function with a specific verb and resource: 'Projections climatiques long terme par scénario IPCC (RCP AR5 + SSP AR6) pour toute localisation.' It also enumerates specific scenarios, horizons, and metrics, which unambiguously distinguishes it from siblings like weather_climate_intel.

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 provides explicit use cases: 'Usages : TCFD/CSRD physical risk, due diligence actifs long terme, assurance catastrophe, planification infrastructure.' This gives clear context for when to use the tool, though it does not explicitly mention alternatives or when not to use it compared to sibling tools.

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