set_task_priority

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

With no annotations provided, the description carries the full burden and does a good job: it discloses CAS-based conditional updates, an audit Event side effect, and the advisory, non-blocking semantic. It could add failure behavior for CAS mismatches or permission requirements, but the core behavioral profile is clear.

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 three short, dense sentences with the main action front-loaded. The second sentence earns its place by clarifying the advisory nature and preventing misuse. There is no redundancy or filler.

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 7-parameter mutation tool with no annotations and no schema descriptions, the description explains the intent well but omits operational preconditions an agent needs, such as how to obtain expected_revision, what role values are valid, and how plan_id is scoped. The output schema helps with return values, but invocation details remain incomplete.

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 schema has 0% parameter description coverage, so the description must compensate. It adds useful semantics for priority (P0-P3), expected_revision (CAS), and task_id (pending task), but it leaves actor_id, role, reason, and plan_id to be inferred from names and the audit context. This is partial compensation, not complete.

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 names a specific verb and resource: 'Set a pending task's advisory P0-P3 priority'. It also states the two key mechanisms, CAS and an audit Event, and explicitly distinguishes this from work-control operations by saying it does not choose, claim, or block work for any LLM. This clearly differentiates it from siblings like claim_task, edit_task, and update_task.

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 gives clear usage context: it applies to pending tasks, is human-facing backlog guidance, and is not a mechanism for LLM work selection. It implies when not to use it by stating it does not claim or block work, though it does not explicitly name an alternative tool such as claim_task.

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