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clarik_memory_learn

Extract and store confirmed facts from conversations, using only final assistant responses and user verifications to build persistent memory.

Instructions

Extract and store facts from conversation. Strips thinking blocks. Only learns from final assistant responses and user-confirmed facts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYesThe conversation content to extract facts from
sourceYesSource of the content
projectPathNoProject root path for isolation
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses that the tool strips thinking blocks and restricts learning to specific sources, which adds behavioral context beyond the schema. However, it omits details on potential side effects, idempotency, or auth requirements.

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?

Three concise sentences front-load the main purpose and key behavioral traits. Every sentence earns its place with no wasted words. Ideal length for quick comprehension.

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?

Given no output schema and no annotations, the description covers the essential behavioral traits and constraints. It provides enough context for correct use, though it could explain what 'thinking blocks' are and the storage mechanism for completeness.

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 baseline is 3. The description does not provide additional parameter details beyond the schema's descriptions, but the context of 'strips thinking blocks' indirectly informs the content parameter. No further value added.

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?

Description clearly states the tool extracts and stores facts from conversation. It distinguishes from siblings by specifying that it strips thinking blocks and only learns from final assistant responses and user-confirmed facts, making its purpose specific and differentiated.

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

Usage Guidelines3/5

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

The description implies usage context by stating only learns from final assistant responses and user-confirmed facts, but lacks explicit guidance on when not to use it or alternatives among siblings. No mention of prerequisites or preferences.

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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