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

Annotations declare readOnlyHint=true, and the description adds 'Updates: monthly' and the data source ('cloud-provider region-uptime logs') and historical reach ('history to 1976'). This goes beyond the annotation by revealing freshness and methodology. No contradiction.

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 two sentences: first states the return value and fields, second gives use cases and update cadence. No wasted words, all info earns its place.

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?

Since there is no output schema, the description lists the return fields (stress_score, region_scores, etc.) and explains the history parameter in the schema. It even notes the update frequency. Missing details like scale direction and field semantics, but it's sufficient for an agent to select and invoke.

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?

Only one optional parameter, 'days', and the schema description is thorough: it explains the history series behavior and the Gold tier requirement. The main description adds nothing further, but the schema covers it 100%, so baseline 3 applies.

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 'Returns a 0-100 US power-grid capacity-utilization stress score' – a specific verb and resource. It lists the return fields (stress_score, region_scores, etc.) and the inference method (cloud-provider region-uptime logs), making it clear and distinct from sibling tools.

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 'Call when the user asks about grid strain, AI-training demand surges, blackout risk, or regional power tightness, or when timing workload placement, power hedges, or energy-arbitrage entries.' This provides clear context for when to use. It does not mention alternatives or when not to use it, but the guidance is actionable.

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