Get System Dependencies

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

No annotations exist, so the description carries the full behavioral disclosure burden. It explicitly says 'Read-only; no side effects' and explains the satisfaction rule for dependencies, including the control-implementation and manual-attestation conditions. This goes well beyond minimal disclosure, though it does not mention pagination or authorization.

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 three short paragraphs with the core purpose front-loaded, followed by behavioral detail and use cases. Every sentence earns its place; there is no repetition or filler.

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 an output schema exists, the description does not need to explain the return structure. It provides enough context to invoke the tool confidently and understand the dependency-satisfaction semantics. The only notable gap is the unexplained server_version required parameter, which slightly weakens overall completeness.

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 only 50%. system_id is trivially described as 'ID of the system' in the schema, and server_version has no schema description and no mention in the description either. The description does not compensate for the missing server_version semantics, which an agent would need to call this required parameter correctly.

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 states a specific verb and resource: 'Get the cross-model dependency graph for a system.' It then defines what that graph contains—assumptions linked to other member models with satisfaction status—and is clearly distinguishable from sibling tools like link_system_dependency, which creates the links rather than reading them.

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 gives explicit use cases: see which assumptions are met by other models' controls, find unsatisfied dependencies, or check system-level completeness. It also directs the agent to link_system_dependency for creating links, which prevents confusion with the write counterpart. This is strong practical guidance.

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