lookup_ag_opinion

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

With no annotations provided, the description carries the burden of explaining behavior, and it does disclose the key return categories: metadata, extracted cross-links to ND primary-law authorities, and optional text. However, it does not mention edge-case behavior such as invalid or nonexistent opinion numbers, or explicitly state that the operation is read-only, which would be more transparent.

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 compact and front-loaded: the first sentence states the operation and key parameter, the second summarizes the return value. Every sentence adds useful information, with no filler or 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?

The tool is a simple, read-style lookup with three well-documented parameters and an output schema, so the description does not need to enumerate return fields. It adequately covers what the tool returns and the optional text parameter, though it does not clarify how this tool relates to the sibling get_opinion_text or handle not-found cases.

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 input schema already explains all three parameters, including the meaning and defaults of include_text and text_limit. The description only reinforces the role of opinion_number and hints at include_text through 'optionally its text', adding little beyond the schema.

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 uses a specific verb ('Retrieve') with a specific resource ('ND Attorney General opinion') and a precise lookup key ('by its number'), with an example format. This clearly distinguishes it from search-style siblings like search_ag_opinions and citation-focused siblings like get_ag_opinions_citing, even without naming them.

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 makes the intended use clear: use this tool when you have a specific AG opinion number and want the opinion's metadata, cited ND primary-law authorities, and optionally its text. It does not explicitly state when not to use it or mention alternatives, so it stops just short of a 5.

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