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

Annotations already declare readOnlyHint=true. The description adds rich behavioral context: the score is a composite z-score, updated weekly, includes trend/percentile/confidence/methodology_version, and has a 51-year history. This goes beyond the annotations by disclosing the nature and cadence of the data, though it doesn't mention rate limits/auth (not indicated as relevant). 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 three sentences: first states what it returns, second gives usage triggers, third states update frequency. Every sentence earns its place with no redundancy or fluff, and the most important information is front-loaded.

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 simplicity (no required params, read-only, no output schema), the description fully outlines the return payload (score, trend, percentile, confidence, methodology_version) and the optional history behavior (via schema). It is complete for an agent to select and invoke the tool correctly even without an output schema.

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 only parameter 'days' is fully described in the input schema (100% coverage), including its optional history behavior and Gold tier requirement. The description itself does not add any parameter-specific meaning, so per the baseline rule for high schema coverage, a score 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 a specific verb ('Returns') and resource ('0-100 energy-transition demand score'), defining its composition (weekly composite z-score of EIA renewable-generation share) and history (51-year since 1975). It distinguishes itself from sibling tools by naming precise topics like renewable share growth and clean-energy allocation shifts.

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 when-to-use scenarios: 'Call when the user asks about renewable share growth, clean energy adoption, solar/wind expansion, or decarbonization momentum, or when timing renewable-tilt ETF rebalances...'. However, it lacks when-not-to-use guidance or explicit alternatives, so it doesn't fully meet the 5-point criterion of exclusions/alternatives.

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