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

Annotations already declare read-only, idempotent, non-destructive, closed-world behavior, so the lower bound is met. The description adds real context beyond them: the result is capped at 5 guards, the per-guard content is specified, and it explicitly disclaims that output is informational rather than legal advice, which matters for how an agent should relay results. It does not discuss ranking ties or what happens with no matching features/markets.

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 text is short, front-loaded with the output description, then usage, then limits in labeled segments. The first sentence is dense and slightly convoluted ('ranked: each guard in one sentence, how many rules...'), but no sentence is filler. Minor tightening would help.

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 and 0% schema coverage, the description usefully explains the return payload and the 5-item cap. But it omits default behavior when features or jurisdictions are null, which is significant for a planning tool where omitting filters presumably broadens the result. Adequate but leaves a functional gap.

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 0% for three parameters, so the description must carry the meaning. It partially does: 'these AI features and markets' maps to the features and jurisdictions arrays, and 'Returns at most 5 guards' corresponds to limit's default of 5. However, it never states the expected value format for features/jurisdictions (names, codes, slugs) or what happens when they are omitted, which is the main ambiguity an agent faces.

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 concrete output: a ranked shortlist of 'guards' that address the most rules for given AI features and markets, with per-lane rule counts and binding-law locations. The verb ('plan') is implicit in the ranking framing, and the term 'guard' is domain jargon left undefined, but the shape of the result makes the tool's function inferable. It implicitly differs from siblings like explain_rule or search_laws by being a prioritization/planning tool, though it never says so explicitly.

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 'When to use' clause: someone asks what to build first, or how to cover several markets at once. That is a clear triggering context. It does not name when-not-to-use conditions or point to the sibling tools (explain_rule, search_laws) for the cases this tool does not serve, so routing guidance is incomplete.

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