Get Org LLM Fallbacks

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

The annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds no additional behavioral context (e.g., return format, edge cases, permissions), but also does not contradict the annotations. A neutral score is appropriate given the strong annotation coverage.

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 concise sentence of eight words, using precise language without any filler. It front-loads the verb and resource, making it instantly scannable.

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?

The tool is inherently simple: no parameters, read-only, and the description fully states what it retrieves. With strong annotations and low complexity, no additional detail is needed for an agent to invoke 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, so there is no parameter description burden. The schema description coverage is 100% by virtue of having no properties, and the description's 'organization's' implies the scope. The baseline of 4 is earned for this parameter-free tool.

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 uses the specific verb 'Get' and clearly names the resource 'organization's configured LLM fallback chain'. This distinguishes it from the sibling update tool (lyzr_update_org_llm_fallbacks) as the read counterpart.

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 clearly implies read-only retrieval of the fallback chain, which is appropriate for this getter tool. However, it does not explicitly name the sibling update tool or state when not to use it, so it falls short of fully explicit alternative guidance.

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