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get_system_prompt

Generates AI system prompts by injecting prioritized user memories and knowledge base context.

Instructions

Generate a system prompt with user memories and knowledge base context injected. The prompt follows the 'memory-first' retrieval priority: User Memories > Knowledge Base > General Knowledge. Use this to inject CarryMem context into any AI agent's system prompt.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contextNoOptional context/topic to filter relevant memories (e.g., 'database setup', 'coding style'). If empty, returns all memories.
max_memoriesNoMaximum number of memories to include (default 10)
max_knowledgeNoMaximum number of knowledge base entries to include (default 5)
languageNoLanguage for the prompt template: en, zh, or ja (default en)en
Behavior3/5

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

With no annotations, the description carries the full burden. It reveals the retrieval priority (memory-first) and that it injects context, which is useful. However, it does not disclose other behavioral traits such as whether the operation is read-only, authentication requirements, or rate limits.

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 concise with only two sentences. The first sentence defines the core function and retrieval order, and the second provides usage guidance. No unnecessary information is included.

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 the 4 parameters and no output schema, the description covers the purpose and retrieval priority well. However, it could be more explicit about the return format (e.g., the type of output), but the tool name and context make the output fairly obvious.

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 coverage is 100%, so the baseline is 3. The description does not add additional meaning beyond what the schema already provides for each parameter; it only summarizes behavior.

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 that the tool generates a system prompt with injected user memories and knowledge base context, specifying the retrieval priority. It distinguishes itself from sibling tools by focusing on system prompt generation rather than memory recall or management.

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 explicitly says 'Use this to inject CarryMem context into any AI agent's system prompt,' providing clear guidance on when to use the tool. However, it does not mention when not to use it or present alternatives, leaving some room for improvement.

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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