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nexo_guard_log_repetition

Log when new learning data matches an existing record to track repetitions and reinforce memory retention.

Instructions

Log a learning repetition (new learning matches existing one)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
new_learning_idYesID of the new learning
original_learning_idYesID of the original learning it matches
similarityNoSimilarity score (0-1)
Behavior2/5

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

No annotations are provided, and the description only says 'log', implying a non-destructive record creation. It does not disclose side effects, required permissions, rate limits, or what happens on duplicate entries. Behavioral details are insufficient.

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

Conciseness4/5

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

The description is a single sentence that efficiently conveys the core action. It is front-loaded with the verb and resource, but it is perhaps too brief, sacrificing potential additional context.

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 lack of output schema and the complexity of logging operations (e.g., idempotency, return values), the description is incomplete. It does not address what the tool returns or handles edge cases, and with many sibling tools, differentiation is missing.

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?

The input schema already provides 100% coverage with descriptions for all three parameters. The description adds minimal context ('new learning matches existing one') but does not significantly enhance parameter understanding beyond the schema.

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 clearly states the action ('log') and resource ('learning repetition'), with context that it involves a new learning matching an existing one. However, it does not differentiate from sibling tools like nexo_learning_add or nexo_guard_check, which could have overlapping purposes.

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?

There is no guidance on when to use this tool versus alternatives (e.g., nexo_learning_add, nexo_guard_check). The description does not mention prerequisites, exclusions, or typical scenarios.

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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