claim_reward_points

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

Annotations only provide generic flags; the description adds crucial behavioral detail: manual awards cannot be undone through the API, unclaim returns 404, negative points are rejected with 400, and compensating via spend_reward_points inflates spent statistics. This is meaningful context beyond what annotations or schema provide.

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 dense and front-loads purpose before caveats. The issue reference and verification date add credibility, though they make the description slightly more verbose than strictly necessary.

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?

Together with the full schema and output schema, the description covers the key decision points: when to call this tool, what happens after mark_done, and the irreversible nature of manual awards. No critical invocation detail is missing.

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 description coverage is 100%, so the schema already documents all parameters thoroughly. The description reinforces the significance of item_id='MANUAL' and positive point values but does not introduce new parameter-level details beyond the schema.

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 ('Award') and resource ('reward points for a completed task or manually'). It clearly distinguishes itself from siblings like spend_reward_points and unclaim_reward_points by scoping what this tool does.

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?

Explicitly explains when to call this tool: after mark_done, because mark_done does not automatically award reward points. It also warns that manual awards are irreversible and names the only compensation path, spend_reward_points, giving clear context for choosing alternatives.

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