get_functional_satisfaction_groups

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

No annotations are provided, so the description takes full responsibility. It explicitly declares 'Read-only; no side effects,' describes the AND/OR group semantics, and details return contents including ungrouped tests. This is thorough behavioral disclosure.

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?

Well-structured with three concise paragraphs: purpose, semantic explanation, and usage guidance. Every sentence adds value, especially the necessary explanation of AND/OR group logic. Front-loaded with the core action.

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 read tool with an output schema, the description provides complete context: what it reads, the grouping semantics, return contents, and when to use it. It also connects to sibling tools, making it self-sufficient for an agent to select and invoke.

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 67%, so the baseline is 3. The description does not add significant parameter-level detail beyond the schema; it explains the domain concept of satisfaction groups but not the parameters themselves, though it reinforces the role of functional_objective_id.

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 opens with a specific verb and resource: 'Read the satisfaction-group structure for a functional objective.' It clearly distinguishes from siblings by naming get_control_assumption_groups and get_mitigation_groups as analogs, and explains what the tool returns.

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 states when to use: 'Use before set_functional_satisfaction_groups to see the current structure, or to trace why an objective is / isn't satisfied.' It also names sibling analogs, providing clear contextual guidance.

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