assume_control

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

No annotations are provided, so the description carries the full burden. It explains that the assumption is written as sole member to group 1, the control counts as active when assumption is active/attested, the AI relevance gate behavior, and that no override is possible. It does not mention side effects on existing groups, but the detailed behavior is well covered.

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 slightly long but information-dense and well-structured. It front-loads the main purpose, then details effects, AI gate, and alternatives. Every sentence adds value, but a minor reduction in wordiness could improve conciseness.

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 complexity (4 required params) and presence of an output schema, the description covers the core behavior, AI gate, error handling, and alternatives. It does not describe return values, but that is acceptable because an output schema exists.

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 coverage is 75% (three of four params described). The description does not add meaning beyond the schema; it only uses the parameter names contextually. The 'server_version' parameter is not described in either schema or description. Baseline of 3 is appropriate.

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 verb ('Mark') and the resources (control and assumption), and distinguishes from sibling tools like 'set_control_assumption_groups' and 'unassume_control'.

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 explicitly tells when to use this tool vs the alternative 'set_control_assumption_groups' for compound cases, and provides guidance on resolving AI gate rejections.

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