cancel_refresh

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

Annotations already declare destructiveHint=true, so the destructive nature is covered by structured data. The description usefully adds the state precondition (QUEUED or RUNNING) and the blocking rationale, but says nothing about what happens to partially ingested data, whether the cancellation is final, or what error occurs if the ingestion is already complete or not found.

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 core action is front-loaded in the first sentence, with two short follow-up sentences that each add distinct value (state precondition, motivation). No filler or restatement of the name.

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?

An output schema exists, so return-value explanation is unnecessary, and parameters are fully covered by the schema. The description supplies the state and motivation context an agent needs to decide to call it; only post-cancellation behavior/error cases are absent.

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 both dataset_id and ingestion_id are already documented, including the hint that ingestion_id comes from refresh_dataset or list_recent_refreshes. The description adds no parameter-level detail beyond the schema, which matches the baseline for fully covered schemas.

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 (Cancel) and resource (a running SPICE dataset refresh), scoped to the ingestion rather than the dataset definition itself. This clearly distinguishes it from siblings like refresh_dataset (which starts an ingestion) and get_refresh_status (which only reads state).

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?

Gives explicit when-to-use conditions: ingestions stuck in QUEUED or RUNNING, and the motivating scenario where old ingestions block new ones. It does not explicitly name or compare against alternatives such as get_refresh_status or letting the ingestion finish, so it stops short of full alternative routing.

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