analyze_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. It discloses that the tool recommends specific categories (AI tools, skills, MCP servers, rules), which is adequate. However, it does not mention any behavioral traits like rate limits, authentication, or side effects, leaving gaps in transparency.

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 two sentences, front-loading the action and then providing usage context. Every sentence adds value with zero fluff.

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 no output schema and simple parameters, the description covers the main purpose and usage. It does not detail the return format, but for a recommendation tool, the context is reasonably complete. A slightly higher score would require output structure hints.

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%, so the baseline is 3. The description does not add significant meaning beyond the schema; it mentions the categories of recommendations which align with the 'focus' parameter enum but does not explain parameters in more detail.

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 analyzes a technology stack and recommends complementary AI tools, skills, MCP servers, and rules. This distinguishes it from siblings like 'recommend' which may be broader, and 'search' which is for searching resources.

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 explicitly says 'Use this when the user describes their project, tech stack, or development environment and could benefit from AI-powered tools.' This provides clear context but does not specify when not to use or mention alternatives, so it misses the full guidance for a 5.

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