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structured_argumentation

Construct and analyze structured debates by specifying claims, premises, and argument types to guide logical reasoning and counterarguments.

Instructions

Dialectical reasoning and argument analysis for structured debates and logical reasoning.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
claimYesThe central claim or assertion being made.
premisesYesA list of reasons or evidence supporting the claim.
supportsNoA list of argument IDs that this argument supports.
strengthsNoA list of the argument's strengths.
argumentIdNoA unique identifier for this argument.
conclusionYesThe logical conclusion drawn from the premises.
confidenceYesA confidence score (0-1) in the validity of the argument.
respondsToNoThe ID of the argument to which this one is responding.
weaknessesNoA list of the argument's weaknesses.
contradictsNoA list of argument IDs that this argument contradicts.
argumentTypeYesThe type of argument being made.
nextArgumentNeededYesA flag indicating whether another argument is needed to continue the debate.
suggestedNextTypesNoA list of suggested types for the next argument.
Behavior2/5

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

No annotations are provided, and the description does not disclose behavioral traits such as side effects, required permissions, limitations, or what happens to existing data. The tool likely creates or retrieves argument structures, but this is not clarified.

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

Conciseness3/5

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

The description is a single sentence, which is concise but lacks structure. It does not front-load key information or separate usage context from details. It could be more informative without becoming verbose.

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 tool has 13 parameters (6 required) and no output schema, the description is too brief to provide complete context. It does not explain how the argument types relate, the purpose of the arguments, or what the tool returns or creates.

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

Parameters3/5

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

Schema description coverage is 100%, so each parameter has a description in the schema. The tool description adds no extra meaning beyond what the schema provides, such as explaining the dialectical flow or relationships between parameters like 'respondsTo' and 'contradicts'.

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

Purpose3/5

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

The description states 'dialectical reasoning and argument analysis for structured debates and logical reasoning,' which indicates the tool's domain but lacks a specific verb indicating what action the tool performs (e.g., 'generate', 'evaluate', 'analyze'). The purpose is somewhat clear but vague compared to sibling tools like 'debugging_approach' or 'scientific_method'.

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 on when to use this tool versus alternatives. The description does not mention prerequisites, when not to use it, or differentiate it from siblings like 'collaborative_reasoning' or 'critical_thinking'.

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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