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forget

Remove specific facts from a knowledge base with cascading retraction of derived information via Truth Maintenance System. Optimizes data accuracy by eliminating outdated or incorrect entries.

Instructions

Retract a fact from the knowledge base. Any knowledge that was derived from this fact is also automatically forgotten via the Truth Maintenance System (cascading retraction). This is the inverse of 'tell'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
predicateYesThe relationship to forget
argsYesThe specific entities to forget about
scopeNoOptional scope
Behavior5/5

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 effectively describes the cascading retraction behavior via the Truth Maintenance System, which is a critical behavioral trait beyond basic functionality. This provides important context about the tool's destructive nature and side effects.

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 perfectly front-loaded with the core functionality in the first sentence, followed by important behavioral context, and concludes with sibling positioning. Every sentence earns its place with zero wasted words.

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

Completeness4/5

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

For a destructive operation with no annotations and no output schema, the description provides good coverage of the tool's behavior and purpose. However, it could benefit from mentioning potential consequences or limitations of the cascading retraction, given the tool's complexity and destructive nature.

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 the schema already documents all three parameters. The description doesn't add any specific parameter semantics beyond what the schema provides, such as examples of valid predicates or how the scope parameter affects the operation.

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

Purpose5/5

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

The description clearly states the specific action ('retract a fact') and resource ('knowledge base'), and explicitly distinguishes it from sibling tools by mentioning it's the inverse of 'tell'. This provides precise differentiation within the toolset.

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

Usage Guidelines4/5

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

The description provides clear context by stating this is the inverse of 'tell', which helps position it relative to at least one sibling. However, it doesn't explicitly mention when to use alternatives like 'retract_pattern' or 'delete_scope', nor does it provide exclusion criteria.

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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