recommend_frontend_stack

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

Annotations already declare readOnlyHint=true and idempotentHint=true, covering safety. The description adds behavioral context by specifying the return content (recommendation, trade-offs, incompatibilities, plan, sources) and the fact vs. inference distinction, which helps the agent set expectations. No contradiction with annotations.

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 long sentence that front-loads the core purpose and then enumerates inputs and outputs. It is efficient with no filler, though splitting into two sentences would improve readability slightly.

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 output schema exists and annotations are present, the description covers the essential purpose, inputs, and output structure well. It lacks explicit usage alternatives and deeper parameter explanations, but overall it provides sufficient context for correct invocation.

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, but it only lists parameter names without explaining semantics or formats. For example, it does not say what 'requirements' should look like, how 'constraints' should be structured, what 'limit' does, or any parameter-specific guidance. The mention of parameters adds minimal value beyond the schema types.

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 a specific action with a clear target: 'Recommend a frontend stack' and lists all relevant input dimensions (requirements, target_framework, constraints, aesthetics, accessibility, performance). It distinguishes itself from siblings like compare_frontend_options (which compares) and build_frontend_brief (which builds brief) by focusing on recommendation and specifying outputs.

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 usage context is implied by the description (use when you have these inputs and need a recommendation), but it does not explicitly state when to use this tool versus alternatives such as compare_frontend_options or search_frontend_knowledge. There are no exclusions or 'when not to use' guidance.

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