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

The annotations already declare read-only, non-destructive, non-open-world behavior, so the description's main addition is the NOT_DATED caveat and the mention of output categories like edition state and semantic diff. It still does not explain output structure, limitations, or why idempotentHint is false, leaving meaningful behavioral context undisclosed.

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 short and front-loads the main purpose in the first sentence. Some internal shorthand ('O-2', 'D1 projections') is less useful than plain language, but the text is not bloated.

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?

There is no output schema, so the description must carry more weight in explaining return values. It names the output categories and one important verdict caveat, but leaves undefined terms and the full shape of results or error cases unexplained.

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%, and the description only conceptually frames the parameters as an instrument and two law dates. It adds no format or constraint details beyond what the schema already provides, so the baseline 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 the core operation: showing what changed in an instrument between two law dates, including edition state, norm dating, and semantic diff. This distinguishes it from law_ask for point-in-time questions, though jargon such as 'axis of editions (O-2)' and 'D1 projections' is opaque without context.

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?

It gives an explicit routing rule for a key alternative: a particular question on a date should use law_ask with legalTime. However, it does not compare against other possibly relevant siblings such as law_inspect, law_query, or law_packages.

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