recommend_stack

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It adds useful behavioral context by stating it scores 40+ technologies across 8 criteria plus environment fit, but it does not explain what the output looks like, how scores are weighted, whether the recommendation is ranked, or any limitations.

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 compact and well-structured: the first sentence states the core purpose and inputs, the second adds the scoring methodology without redundancy. Every sentence earns its place and the key function is front-loaded.

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?

This is a complex tool with 16 parameters, no annotations, and no output schema, but the description does not explain the return value, ranking behavior, or how environment fit is computed. An agent could invoke it with the required fields, but it lacks enough context to fully anticipate the tool's recommendation format or edge-case behavior.

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 100%, so the baseline of 3 applies. The description references categories like deployment environment, target devices, network conditions, and infrastructure constraints, but these already appear in the schema and no additional parameter meaning or interaction details are provided beyond the structured definitions.

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 identifies the verb (recommend), resource (technology stack), and the key considerations (deployment environment, target devices, network conditions, infrastructure constraints). It is not a tautology and conveys a specific function, though it never explicitly distinguishes itself from overlapping siblings like compare_tech or recommend_dual_stack.

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 when to use the tool (when selecting a stack under environmental and infrastructure constraints) but gives no explicit guidance about when not to use it or which sibling tools to choose instead. With siblings such as compare_tech, recommend_dual_stack, and analyze_compatibility present, the lack of routing guidance 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.