adjust_customer_member_points

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

Despite no annotations, the description discloses key behavioral traits: immediate balance change, transaction history recording, and potential error on insufficient points. This exceeds expectations and provides sufficient 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 well-structured with sections for purpose, API call, return structure, and side effects. It is concise but includes some extraneous details (e.g., the exact API endpoint) that may not be necessary for an AI agent.

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 simple parameter set (3 parameters, no nested objects, no output schema), the description covers purpose, behavior, side effects, and return structure adequately. It is complete for the tool's complexity.

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 100% coverage with clear descriptions for each parameter. The description adds no additional parameter semantics beyond what the schema provides, so baseline score 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?

The description clearly states the tool's action ('adjust customer member points') and explicitly mentions it can add or deduct points, with specific use cases like manual compensation or activity rewards. It is distinct from sibling tools, as no other tool focuses on adjusting member points.

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 clear use cases (manual points addition, activity rewards, complaint compensation) via a dedicated section. It implies when to use the tool, though it does not explicitly state when not to use it. However, given the distinct function, this is adequate.

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