CSL-Core

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes what the tool returns (structural information, coverage analysis, visualization) and its purpose (analysis, planning, cost estimation), which adds useful context. However, it lacks details on performance characteristics (e.g., computational cost, timeouts), error handling, or side effects, which are important for a tool analyzing policy state spaces.

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 and appropriately sized. It starts with a clear purpose statement, lists return values in bullet points for readability, explains usage context, and specifies the single parameter concisely. Every sentence adds value without redundancy, making it easy to scan and understand.

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 tool's complexity (analyzing policy state spaces), no annotations, and the presence of an output schema (which handles return values), the description is mostly complete. It covers purpose, usage, and parameter semantics adequately. However, it could benefit from more behavioral details (e.g., performance limits) to fully guide an agent, especially since annotations are absent.

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%, so the description must compensate. It adds meaning beyond the schema by explaining that 'csl_content' is 'The complete CSL policy source code as a string,' clarifying the format and content expected. However, it does not provide examples, constraints (e.g., length, syntax), or validation details, leaving some gaps in parameter understanding.

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's purpose: 'Analyze the state space "universe" of a CSL policy.' It specifies the exact resource (CSL policy state space) and verb (analyze), and distinguishes it from siblings like 'explain_policy', 'simulate_policy', and 'tla_verify' by focusing on structural analysis rather than explanation, simulation, or verification.

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 clear context for when to use this tool: 'Essential for understanding the "universe" an agent lives in, planning Evolving Universe experiments, and estimating TLC verification cost before running tla_verify.' It implicitly suggests alternatives (e.g., use 'tla_verify' for actual verification) but does not explicitly state when not to use it or name specific sibling tools as alternatives.

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