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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds genuine behavioral context beyond that: always-applicable rules are pre-delivered at conversation start, which shapes what the agent should expect from this call. It stops short of describing the returned shape or ordering, but no output schema exists to cover that either.

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?

Two tight sentences, no filler, with the core action first and the usage condition second. Every clause carries information the agent needs.

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 single-optional-parameter read tool with no output schema, this covers purpose, trigger, and the key behavioral quirk. A minor gap remains around whether always-applicable rules appear in the result set versus being omitted, which would remove the only real ambiguity.

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% and the schema already says the filter is optional and omitting it lists everything. The description adds meaning the schema lacks: the scope corresponds to project-scoped rules, clarifying what values are meaningful for that parameter.

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 ('List the user's saved rules') and immediately distinguishes this read operation from the mutation siblings add_rule/update_rule. The note that always-applicable rules are already delivered at conversation start further separates it from the context-delivery siblings like briefing.

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 an explicit trigger ('call this only when the user asks what rules they have, or asks about rules scoped to a specific project') and an implicit exclusion (don't fetch always-applicable rules, they arrive automatically). This is exactly the when/when-not routing an agent needs.

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