assume_for_step

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

With no annotations, the description carries the burden. It describes input format (alternating strings) and return values (updated assumptions and conflicts), but omits side effects, idempotency, error conditions, or parameter constraints. Adequate but not thorough.

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 concise with clear sections (Args, Returns) and an emoji header. However, the inconsistency with the schema detracts from its effectiveness. It is not excessively long but could be more precise.

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?

With an output schema present, return description is adequate. The parameter description is incomplete due to schema mismatch. Given the complexity of assumption management and many sibling tools, more detail on the expected string format would improve completeness.

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 0%, so description must compensate. It explains that 'args' should be alternating symbol and property strings, which adds meaning. However, there is a mismatch: description implies variadic positional arguments ('*args') while schema defines a single string property. This inconsistency may confuse an AI agent, reducing clarity.

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 tool name 'assume_for_step' and description 'Set assumptions for the current derivation step only' clearly indicate a step-scoped assumption-setting operation, distinguishing it from a global 'assume' tool. The addition of 'only' further emphasizes the scope.

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 does not mention when to use this tool versus siblings like 'assume', 'check_assumption_conflicts', or 'clear_step_assumptions'. No explicit guidance on alternatives or scenarios where this tool is inappropriate.

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