universe_info

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

With no annotations, the description carries the full burden. It lists what the tool returns (variables, domains, constraints, etc.) and implies a read-only analysis. However, it does not explicitly state no side effects or potential costs, leaving a minor 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 well-structured with a clear purpose statement, bullet-pointed outputs, usage context, and parameter definition. It is slightly lengthy but each part adds value, earning a high score.

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?

Given the presence of an output schema, the description adequately explains input semantics, high-level outputs, and when to use the tool. It covers prerequisites and implications for verifying CSL policies, providing a complete picture for an AI agent.

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 schema has 0% description coverage, but the description provides full semantic meaning for the sole parameter 'csl_content', stating it must be the complete CSL policy source code as a string.

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 tool analyzes the state space 'universe' of a CSL policy, which is a specific verb and resource. It distinguishes from siblings like 'explain_policy' and 'tla_verify' by focusing on structural analysis of the state space.

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 explicitly states when to use the tool: for understanding the universe, planning experiments, and estimating verification cost before running 'tla_verify'. This provides clear guidance on usage context and alternatives.

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