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icemaple77

HCC

store_memory

Persist a new memory for an agent, attaching optional metadata like type, summary, importance, and tags to support context-aware retrieval.

Instructions

Store a new memory in HCC.

Args: content: The memory text to store (required). user_id: Owner of the memory (e.g. "michael"). agent_id: Which agent this memory belongs to (e.g. "hanyan", "hermes", "openclaw-main"). Memories are scoped by agent_id — different agents don't see each other's memories unless explicitly queried across agents. type: Memory category, e.g. "general", "knowledge", "fact", "preference". summary: Optional short summary of the content. importance: Relevance score in [0, 1]. Defaults to 0.5. tags: Optional list of string tags. embedding: Deprecated, ignored. The server always computes its own embedding (ollama, server-side) so every memory lands in the same vector space — kept only so old callers that still pass one don't break.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNo
typeNogeneral
contentYes
summaryNo
user_idNodefault
agent_idNodefault
embeddingNo
importanceNo
Behavior4/5

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 does an excellent job: it explains that the embedding parameter is deprecated and ignored, that the server computes its own embedding, and that memories are scoped by agent_id. This goes beyond the schema and provides critical behavioral context for the agent.

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 well-structured with a clear opening line and a bulleted parameter list. It is slightly verbose due to the detailed parameter explanations, but every sentence adds value, especially the deprecation note and scoping explanation. It is appropriately sized for an 8-parameter tool.

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

Completeness5/5

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

Given the tool's complexity (8 parameters, no annotations, no output schema), the description is remarkably complete. It covers all parameters, explains scoping, deprecation, and defaults, and provides examples. The agent has everything it needs to invoke the tool correctly without additional context.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must compensate, and it does thoroughly. Every parameter is explained with examples and constraints (e.g., importance range, agent_id examples, type categories, embedding deprecation). This adds significant meaning beyond the raw schema, which only provides types and defaults.

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 tool's purpose: 'Store a new memory in HCC.' It uses a specific verb ('store') and resource ('memory in HCC'), and the detailed parameter explanations distinguish it from sibling tools like search_memories, recall, and delete_memory, which are all about retrieval or deletion.

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 on when to use the tool (to store a new memory) and explains the scoping behavior of agent_id, which is crucial for understanding how memories are isolated. However, it does not explicitly mention when not to use it or name alternative tools for similar operations, though the sibling list makes that implicit.

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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