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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals that the tool performs adversarial perturbations and returns a Robustness Index plus hardened paths, which is useful. However, it does not mention side effects, mutability, input requirements, or failure modes. For a computation-oriented tool this is moderately transparent but incomplete.

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 a single, dense sentence with no wasted words. It front-loads the core action and outcome, making it easy to scan. Every term contributes meaning, and there is no redundant or filler content.

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?

Despite having an output schema, the description lacks essential context for a 6-parameter tool with zero annotations and zero schema coverage. It introduces domain jargon (lattice, Robustness Index, hardened paths) without definitions, does not clarify parameter semantics, and provides no guidance on when or how to use the tool. An agent would struggle to call this tool correctly based solely on this description.

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 hints at 'trajectories' and 'perturbations', which maps loosely to the trajectory and stress_amplitude/max_perturbations parameters, but it does not explain lattice_id, lattice_data, step_budget, or how the parameters interrelate. This is insufficient for correct invocation with 6 optional parameters.

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 action ('Subject candidate trajectories to adversarial algebraic perturbations') and a concrete outcome ('calculate Robustness Index (R) and project hardened paths'). It clearly identifies the tool's purpose and distinguishes it from generic compute tools, though it does not explicitly contrast with sibling tools such as cognitive.counterfactual_what_if or cognitive.project_to_manifold.

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?

There is no guidance on when to use this tool versus alternatives, no mention of prerequisites, and no stated exclusions. The description only says what the tool does, not when an agent should choose it. With many cognitively-themed siblings, this is a notable gap.

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