algo_generate_edge_cases

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

Since no annotations are provided, the description carries the full burden for behavioral transparency. It lists the types of edge cases generated but does not disclose the return format (e.g., array of test cases), determinism, or any side effects. The tool is a generator, but the description doesn't clarify what the output looks like, which is essential for an agent to use it correctly.

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 sentence with a clear verb and concrete examples, front-loading the purpose and key characteristics. There is no redundancy or unnecessary detail, making it highly efficient for an agent to parse.

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 has no output schema and no annotations, the description should explain what the tool returns and how the output can be used. It does not mention the number of cases generated, the output format, or any other behavioral details. The description is adequate for understanding the general purpose but insufficient for an agent to know what to expect when invoking the tool.

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 both parameters (maxN, type) described. The description adds some context by linking edge case examples to parameter types (e.g., disconnected graphs for graph type), but it doesn't explicitly explain how maxN or type affect the generation output. With full schema coverage, a score of 3 is baseline; the description provides marginal additional value.

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: it generates adversarial corner cases, and it lists concrete examples (min N=1, max bounds, identical items, extreme negatives, disconnected graphs). It distinguishes itself from sibling tools like algo_stress_test, which presumably generate random or stress test cases, by focusing on adversarial edge cases. The verb 'generates' is specific and the resource is well-defined.

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 implies usage for testing purposes (generating edge cases to complement other testing tools) but does not explicitly state when to use it versus alternatives like algo_stress_test or algo_run_sandboxed. It lacks when-not guidance or mention of alternative tools. Usage is implied but not directly articulated.

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