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Generate physical hypotheses

generate_hypotheses
Read-onlyIdempotent

Explores candidate transformations from the same PhysicalProblem and labels every unverified candidate as HYPOTHESIS.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
descriptionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
toolYes
factsYes
statusYes
warningsYes
requestIdYes
confidenceYes
provenanceYes
schemaVersionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds useful behavioral context: it explores candidate transformations, focuses on the same PhysicalProblem, and labels only unverified candidates as HYPOTHESIS. The word 'labels' could be slightly ambiguous, but it is consistent with read-only exploration if interpreted as labeling in the returned output rather than persisting state.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, tightly worded sentence that front-loads the core behavior and outcome. There is no redundant filler or repetition of the tool name or title.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the one parameter with zero schema coverage and the need to distinguish among many sibling tools, the description leaves important gaps: it does not explain the input parameter, usage conditions, or how this step relates to verification and synthesis. The output schema exists, so return values need not be detailed, but the input semantics and invocation context are insufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must explain what the single 'description' parameter means, but it never mentions it. An agent would not know whether 'description' refers to a problem statement, a hypothesis description, or some other input. The description says 'from the same PhysicalProblem' but does not connect that to the parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('explores candidate transformations') and a clear outcome ('labels every unverified candidate as HYPOTHESIS'), tied to the same PhysicalProblem. It is clear about the tool's role, though it does not explicitly contrast with sibling tools such as verify_solution or synthesize_physical_solution.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance is given about when to use this tool versus alternatives like verify_solution, resolve_problem, or synthesize_physical_solution. The description implies an exploratory hypothesis-generation step, but it does not state prerequisites, follow-up steps, or situations where another tool should be chosen instead.

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

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