get_flavors

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

No annotations are provided, so the description carries the full behavioral burden. It discloses that the tool returns flavor names and IDs and scopes results to 'all available' flavors, implying a safe read operation. It does not cover permissions, caching, or ordering, but for a zero-parameter list tool the behavior is reasonably self-evident.

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?

Two short sentences with zero waste. The purpose is front-loaded in the first sentence, and the second sentence adds return-format and usage value without repetition. Every word earns its place.

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 simple, zero-parameter tool with an output schema present, the description is adequately complete. It states the purpose, what it returns, and why it matters. The output schema covers return values, so nothing essential is missing for an agent to call it correctly.

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 tool has zero parameters, which per the rubric establishes a baseline of 4. There is nothing for the description to supplement since the input schema is trivially complete at 100% coverage. No deduction applies.

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?

States a specific verb (List) and resource (platform flavors) with explicit scope ('all available on ALBS'). It distinguishes itself from the sibling get_platforms by specifying 'platform flavors' rather than the ambiguous 'platforms', and from get_products by naming the flavor domain. An agent can tell exactly what this returns without opening anything else.

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?

Provides a concrete usage context: verifying correct flavor names before creating builds with the flavors parameter, which routes toward the sibling create_build workflow. It does not explicitly name alternatives or state when not to use the tool, so it stops just short of a 5.

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