quantaoptima_benchmark

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

No annotations are provided, so the description carries the full burden. It does disclose genuine behavioral context: three specific optimizers are run, they share the same evaluation budget, and results are returned side-by-side, plus a Pro-license access requirement. However, it omits runtime cost, whether it is compute-heavy or long-running, and any rate or resource implications.

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 purpose and mechanism are front-loaded in the first three sentences, followed by a compact Args block. The embedded Stripe purchase URL is slightly promotional noise, but it is relevant to the stated Pro-license requirement, so little is wasted overall.

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?

An output schema exists, so return values need not be described, and the description adequately covers purpose, mechanism, and all three parameters with ranges. The main gap is the absence of usage routing against siblings and any runtime/behavioral expectations for a multi-optimizer run.

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, and it largely does: objective enumerates the valid built-in functions (sphere, rastrigin, rosenbrock, ackley, griewank, levy), dimensions gives the 2-50 range, and max_evals gives the 1000-50000 budget range. This adds meaning the bare schema lacks, though defaults (rastrigin/10/5000) are not restated.

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 and resource: 'Compare QuantaOptima against classical optimizers on the same problem,' naming the exact algorithms (QuantaOptima, Differential Evolution, Dual Annealing) and the equal-budget constraint. This distinguishes it from the sibling quantaoptima_optimize, which presumably runs a single optimizer rather than a head-to-head comparison.

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 a benchmarking use case and notes a Pro-license precondition, but never explicitly says when to choose this over quantaoptima_optimize or when a comparison is warranted. Usage is inferable from the word 'Compare' but not spelled out with exclusions or a named alternative.

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