Decision alignment check

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

Annotations declare readOnlyHint=true, so the safety profile is known. The description adds the behavioral guidance to call before changes, but doesn't disclose return format, rate limits, or what happens if no decisions are recorded. Adds some value beyond annotations but leaves gaps.

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?

Two tightly written sentences: first states what it does, second states when to use it. No wasted words, front-loaded purpose.

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 read-only check with fully documented parameters and no output schema, the description covers purpose and timing. It could mention what the check returns (e.g., aligned/misaligned) or how to interpret results, but is largely 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?

Schema coverage is 100%, with each parameter having a clear description and examples. The description itself adds no parameter details, so it meets the baseline 3 when schema does the heavy lifting.

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?

States a specific verb (check) and resource (alignment with recorded decisions), and distinguishes itself from siblings like dependency_check and decision_memory by naming what it validates. It doesn't explicitly differentiate from decision_memory, which likely stores decisions, but the purpose is clear.

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?

Explicitly tells the agent when to call: 'BEFORE suggesting a major tech change, new library, or architecture shift.' This is a clear pre-action trigger that no sibling provides.

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