hypothesis_create

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses one important behavioral trait: the tool does not auto-promote to invariant/decision, which is a meaningful constraint. However, it does not disclose other behaviors such as side effects, required permissions, or what happens on successful creation. The single behavioral note is useful but not comprehensive.

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 extremely concise: two sentences with zero wasted words. The primary purpose is front-loaded in the first sentence, and the critical behavioral constraint is stated in the second. Every word earns its place, achieving maximal clarity with minimal length.

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 tool has 10 parameters, 4 required, and zero schema descriptions, the description is grossly inadequate. It provides no guidance on parameter semantics, field relationships, or expected input format. Even though an output schema exists, the agent cannot correctly construct a call without understanding the parameters. The description is far too thin for a tool of this complexity.

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 0%, meaning the input schema provides no descriptions for any of the 10 parameters. The description adds no parameter-specific information whatsoever—it does not explain what 'statement', 'hypothesis', 'confidence', or 'evidence_for' mean, nor which fields are required. With such a gap, the agent has no guidance on how to populate the parameters, making this dimension critically weak.

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 and resource: 'Create a hypothesis memory.' It also implies a distinction from invariant/decision tools via the 'Never auto-promote' clause, but it does not explicitly contrast with other memory creation siblings like assumption_create or observation_create, so it is not fully differentiated. Still, the purpose is unambiguous.

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 instruction 'Never auto-promote to invariant/decision' explicitly tells the agent when not to use this tool (for invariants/decisions) and implies it is for hypotheses that should remain tentative. It does not mention alternative tools for assumptions or observations, but it does provide a clear exclusion for two key siblings, which is helpful guidance.

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