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

With no annotations, the description carries the full burden and does so substantively: it discloses the free/Pro data-window constraint, that values are exact as published with unit/date/source URL, that incomplete days are flagged rather than filled, and the licensing terms (free non-commercial with attribution, commercial requires Pro). It omits rate limits and refresh cadence, but the disclosure of access boundaries and data-integrity behavior is strong.

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?

Dense but front-loaded: it leads with what the data is, then the access window, then integrity/licensing. Every sentence carries information, though the free-window constraint is stated twice (latest month and 'most recent 30 days'), a minor redundancy.

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 an 8-parameter, no-output-schema tool with no annotations, the description covers the critical context: data domains, free vs Pro window, data-integrity guarantees, and output-value shape (unit, date, source URL). Parameter mechanics are delegated to a fairly complete schema, so the definition is close to complete without redundancy.

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 coverage is 75%, so the schema already documents most parameters (end, limit, start, sector, series, dataset, measure). The description mostly restates the same data domains rather than adding syntax or format meaning beyond the schema. Baseline 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?

States a specific resource (official Texas retail electricity statistics) and enumerates the exact metrics covered (EIA monthly average price, sales, customers, revenue by sector; BLS CPI electricity and all items; BLS price per kWh). This is well beyond a tautology. It does not, however, differentiate itself from siblings like market_catalog or market_us_states, so an agent must infer the boundary.

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 gives meaningful access-tier guidance: the free window is the latest month / most recent 30 days, and a Pro key unlocks full history. That tells the agent when this tool will actually return usable data. But there is no explicit when-to-use-vs-alternative routing (e.g. versus market_catalog), leaving usage largely implied.

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