Generate all possible subsets from an array of up to 20 elements for combinatorics, testing, and exhaustive grouping tasks.
Generate all subsets of a set (up to 20 elements).
| Name | Required | Description | Default |
|---|---|---|---|
| elements | Yes | Array of elements (max 20) |
Changes observed during successful MCP inspections.
v0.1.11Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, so the description carries the full behavioral burden. It discloses the 20-element limit, a critical constraint, but does not describe return format, determinism, or complexity.
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?
One sentence, front-loaded with the core action and constraint. No wasted words.
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 simple, single-parameter math tool with a fully documented schema, the description plus schema is nearly sufficient; the lack of output schema means return format is unspecified, but the operation is standard.
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% and the schema already documents the 'elements' array and its 20-item limit. The description repeats the limit but adds no new semantic meaning.
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 'Generate' and resource 'all subsets of a set', and includes a scoping constraint. This clearly identifies the operation (power set) and differentiates it from sibling combinatorial tools like combination_calc.
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?
No explicit when-to-use, no alternatives, no exclusions. A user must infer usage from the operation itself.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.