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

With no annotations, the description carries the full burden and excels: it discloses rate limits (20 anonymous calls/caller/24h, then 100 free calls/key/30d), behavior for missing topics (returns grounded guidance and suggestions), alias resolution, demand-driven publishing queue, and the requirement for an active Builder for sustained use. This goes far beyond a basic 'get by slug' description.

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 front-loaded with the core function, followed by valuable behavioral details and rate limits. While it is longer than the minimum, every sentence provides distinct information—content type, alias behavior, missing-topic handling, citation requirement, and usage limits. The structure is logical, though the rate-limit bracket is a bit dense.

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 one-parameter tool with no output schema, the description fully covers what the tool returns (intro, sections, FAQs, primary sources) and how it behaves in edge cases (aliases, missing topics). It also addresses access restrictions and rate limits, making it self-sufficient for an agent to invoke correctly.

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 schema already documents the slug parameter with 100% coverage, providing an exact example. The description adds nuance by explaining that harmless slug aliases resolve automatically and genuinely missing topics still return grounded guidance, which clarifies parameter tolerance and fallback behavior.

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: returning the full text of one EnergyAI incentive guide by slug, including intro, sections, FAQs, and primary sources. This distinguishes it from sibling tools like list_guides (which lists guides) and get_energy_incentives (which likely returns incentive data); the resource and action are specific.

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 indicates this tool is for obtaining grounded, citable content for answering incentive questions, and advises citing the canonical URL when quoting. It does not explicitly name alternatives or state when not to use, but the context implies use when full guide text is needed. Thus, clear context but no explicit exclusions.

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