get_system_dependencies

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

Although no annotations are provided, the description explicitly states 'Read-only; no side effects.' It also describes the nature of the return: 'Returns every assumption ... with its satisfaction status.' This fully discloses the behavioral contract, compensating for the lack of annotations.

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 three sentences: purpose, return details, and usage guidance. It is concise but slightly redundant (e.g., 'cross-model dependency graph' repeated as 'cross-model dependency' in the second sentence). Overall, it is efficient and organized.

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?

No output schema is provided for this tool, so the description must cover the return type. It does state that it returns assumptions with satisfaction status, but it lacks details on error behavior, pagination, or the exact structure of the dependency graph. Given the absence of an output schema, the description is not fully complete.

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 includes two parameters: system_id and server_version. Only system_id has a description in the schema; server_version has none. The tool description does not elaborate on either parameter, failing to compensate for the missing server_version description. Thus the parameter semantics are only partially clarified.

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 function: 'Get the cross-model dependency graph for a system.' It uses a specific verb and resource, and the phrase 'cross-model dependency graph' distinguishes it from sibling tools like 'link_system_dependency' or 'get_reachability_verdicts'.

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 provides usage scenarios: 'Use to see which assumptions are met by other models' controls, find unsatisfied dependencies, or check system-level completeness.' This clearly indicates when to employ this tool, and it even points to the complementary tool for creation ('Create these links with link_system_dependency').

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