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

Annotations (readOnlyHint=true, openWorldHint=false) already establish a safe read operation. The description adds valuable context: weekly frequency, 53 years of history, the score composition, and the output fields. It does not mention error handling or rate limits, but for a read-only tool with these annotations, this is sufficient additional transparency.

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, front-loaded with the primary verb and resource, and contains zero filler. The first sentence packs high-value details (formula, frequency, history length, output fields); the second sentence gives actionable usage guidance. Every word 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?

For a simple read-only indicator tool with one optional parameter, the description is complete. It explains the output scale (0-100), lists the returned fields, provides usage context, and the schema handles the only parameter. Since there is no output schema, the description adequately covers return values by naming them.

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 100%, so the optional 'days' parameter is fully described in the schema, including its effect (return a daily history series), maximum value, and tier requirement. The main description adds no parameter details, but with full schema coverage, the baseline of 3 is appropriate.

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 'Returns a 0-100 US industrial electricity-cost squeeze score' with the specific formula (spread of industrial electric-power PPI growth over manufacturing output growth) and output fields (trend, z_score, composite_latest_value, baseline stats). This is a specific verb+resource that distinguishes it from sibling tools, even without naming alternatives.

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?

Provides explicit use cases: 'Call when the user asks about industrial power costs, manufacturer energy margins, or electricity-driven margin compression, or when timing power procurement hedges, energy surcharges, or energy-intensive capacity decisions.' This gives clear context for when to use it, though it lacks explicit when-not-to-use guidance or named alternative tools.

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