GreenLight - Plug-in Solar Law Registry

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

Annotations cover the safety profile (readOnly, idempotent, non-destructive, closed-world), and the description adds genuinely new behavioral context: pending entries are unverified field-by-field, their verification_note says so, and no certification claim is published until an adversarial verification pass. This is exactly the extra context annotations cannot supply.

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?

Front-loads the return content, then covers input, pending-entry caveats, and error behavior. Dense but nearly every sentence carries a distinct fact; the trailing legal-advice/certification sentences are slightly repetitive with earlier caveats but not wasteful.

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?

With no output schema, the description carries the full burden of describing the return shape and does so field-by-field (status, name/dates, provisions, citations, verification status), plus caveats for pending and untracked records. An agent has everything needed to call and interpret this tool.

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 100% for the single parameter, so the baseline is 3. The description adds value beyond the schema by specifying the failure semantics for non-US-state input and the output implication for unregistered states, giving the agent meaning the schema alone does not convey.

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 verb and resource ('Returns the full GreenLight registry record for one state's plug-in solar law') and enumerates the record's contents. It is clearly distinguishable from the sibling solar_states, which the description's singular-state framing implicitly contrasts.

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?

Gives clear usage context: one state lookup via code or full name, plus edge cases — a state absent from the registry returns tracked:false and non-US input is an error. It never explicitly names solar_states as the alternative for enumerating states, so routing is left partly to inference.

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

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

Annotations already establish readOnly, idempotent, non-destructive and closed-world behavior, and the description adds genuinely non-obvious context: pending entries are under review and unconfirmed, absence from the registry is not a legal statement, and the data is not legal advice. That is real disclosure beyond the annotations, though it never describes response format or freshness beyond 'under review'.

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 returned fields are front-loaded in the first sentence, with caveats following in compact clauses; every sentence carries information. It is slightly caveat-heavy but nothing is padding.

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?

With no output schema, the description fully carries the return-value burden by naming the fields and the verification-state count, and it preempts the two most likely agent misreadings (unlisted = no law, and treating the data as legal advice). Complete for a parameterless read tool.

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 has zero parameters, which sets the baseline at 4. The description confirms 'Takes no input', consistent with the empty schema, and adds no misleading parameter expectations.

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 states a specific verb and resource ('Lists every state in the GreenLight plug-in (balcony) solar registry') and enumerates the returned fields (legal status, law name, power cap, verification state, counts). It is clear what the tool does, but it never differentiates itself from the sibling solar_law, so an agent must infer the split from the schema alone.

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?

'Takes no input' establishes that this is an unfiltered list call, and the caveat that unlisted states simply aren't in the registry implicitly frames usage. However, there is no explicit when-to-use guidance or mention of when to prefer solar_law for a single state's law, leaving the routing to the agent.

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