get_pending_rules

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

With no annotations, the description carries the full transparency burden. It clearly states what the tool returns and implies a read-only operation through 'Get'. It adds behavioral context by specifying the source ('proposed by the LLM') and the pending status. It does not mention side effects, but for a getter this is sufficient.

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 two sentences: the first states the purpose, the second gives usage guidance. No filler words, information is front-loaded and every word earns its place.

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 parameterless list tool without an output schema, the description explains what is retrieved and when to call it. It could specify the structure of the returned rules or behavior when no rules are pending, but the scope is clearly defined and sufficient for an agent to invoke it correctly.

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?

The tool has zero parameters, and the input schema is an empty object. The baseline for 0 params is 4, and no further parameter explanation is required.

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 'Get list' and clearly identifies the resource as 'rules proposed by the LLM that are awaiting user approval'. This distinguishes it from sibling tools like list_rules (all rules) and approve_rule/reject_rule (actions).

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 provides an explicit when-to-use: 'Use this after suggesting a rule to show the user what needs approval.' This ties it to the suggest_rule workflow and gives clear context. It does not mention explicit alternatives or when-not-to-use, but the guidance is concrete.

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