stochasticalgorithm

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

No annotations are provided, so the description carries full burden. It mentions 'systematic approach to handling uncertainty' but lacks critical behavioral details: whether this is a read/write operation, computational requirements, error handling, or output format. For a complex tool with 4 parameters, this is insufficient disclosure.

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 well-structured with a clear opening sentence followed by a bulleted list of algorithms and a summary. Each sentence adds value by explaining algorithm purposes. It could be slightly more concise by integrating the list more tightly, but it's generally efficient.

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 complexity (4 parameters, nested objects, no output schema, and 0% schema coverage), the description is incomplete. It doesn't explain what the tool returns, how to interpret results, or detailed parameter usage. For a stochastic algorithm tool with significant input complexity, this leaves too many gaps for effective use.

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 lists algorithm names (mapping to the 'algorithm' enum) and implies 'problem' is a decision-making issue, but doesn't explain 'parameters' object structure or 'result' parameter. This adds some meaning but doesn't fully cover the 4 parameters, especially the complex 'parameters' object.

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: applying stochastic algorithms to decision-making problems. It lists specific algorithms (MDPs, MCTS, etc.) and explains they handle uncertainty, which is more specific than just restating the name. However, without sibling tools, it cannot demonstrate differentiation from alternatives.

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 provides no guidance on when to use this tool versus other approaches. It lists algorithm types but doesn't specify scenarios, prerequisites, or exclusions for usage. There are no sibling tools mentioned, but general context for application is missing.

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