product_manager_get_anti_patterns

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

No annotations are provided. The description does not disclose any behavioral traits like permissions, side effects, or output format. However, since the tool is a simple lookup of a fixed set of anti-patterns, the lack of detail is not critical. It does not contradict annotations as none exist.

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 extremely concise: two sentences that list the anti-patterns and state the use case. Every word adds value. No fluff or redundant information. Front-loaded with key details.

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?

For a tool with no parameters and no output schema, the description sufficiently conveys what the tool does. It covers the content and purpose. However, it might benefit from mentioning the output format or that it returns a textual list. Still, adequate for a simple lookup tool.

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?

The input schema has 0 parameters, so schema coverage is 100%. Per guidelines, 0 parameters sets a baseline of 4. The description adds no parameter details because there are none, so the score reflects the baseline.

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 lists specific codifiable PM anti-patterns (feature-factory, reactivity, etc.) referencing Cagan and Doshi. It says 'Use to flag weak product reasoning,' which defines the purpose. However, it does not differentiate from sibling tools like product_manager_get_four_risks or product_manager_get_jtbd, which could be confused.

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 a use case ('flag weak product reasoning') but does not give explicit when-to-use or when-not-to-use guidance. No alternatives or exclusions are mentioned. It implies usage for identifying anti-patterns but lacks depth.

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