list_rules

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

With no annotations provided, the description carries the full burden of behavioral disclosure, but it remains terse. It does not state whether the operation is read-only, what the return payload looks like (e.g., full rule objects vs. references), or any side effects. The 'HOW' clause hints that the list yields items needing follow-up reads, but this is implicit rather than explicit. For a tool lacking any annotation coverage, this is a significant gap.

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 extremely concise, using a WHEN/HOW structure that immediately conveys the intended trigger and follow-up action. Every word serves a purpose: the WHEN clause sets the invocation condition, and the HOW clause routes to complementary tools. No filler or redundancy exists.

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 simple listing tool with one optional parameter and no output schema, the description covers the high-level purpose and workflow. However, it omits the shape of the returned data (e.g., whether it returns rule IDs, names, or full contents) and any pagination or ordering behavior. Given the HOW hint, an agent can infer that the output is a collection of rule references, but this inference is not explicit and leaves room for misinterpretation.

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%, as the only parameter (skillId) already carries a description ('Filter rules by skill'). The tool description adds no additional meaning or constraints beyond the schema, so it does not enhance the parameter semantics. Per the rubric, a baseline of 3 applies when the schema fully covers parameter meaning.

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 explicitly states the verb 'list' and resource 'UdonSharp rules', making the tool's purpose unambiguous. It further clarifies the timing ('before coding') and implicitly distinguishes from read_rule by framing it as a precursor to reading individual rules. The resource is specific enough to separate it from sibling list tools like list_skills and list_templates.

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?

Provides a clear WHEN condition ('when you need the set of UdonSharp rules before coding') and a directed HOW workflow ('list then read_rule for any rule that applies'). This gives concrete guidance on when to invoke the tool and how to proceed, though it does not explicitly mention alternatives or when not to use it. The workflow implication is strong enough to be considered clear context.

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