Task Router Skill
Task Router
Persistent memory for agents. Stores preferences, decisions, facts, and events as a connected knowledge graph. Recalled by who, what, when, or why.
请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。
SkillHub CLI
skillhub install harshidwasekar/hypabase-memory打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。
将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。
Persistent memory for agents. Stores preferences, decisions, facts, and events as a connected knowledge graph. Recalled by who, what, when, or why.
Add the MCP server to your OpenClaw config (~/.openclaw/openclaw.json):
{
"mcpServers": {
"hypabase-memory": {
"command": "uvx",
"args": ["--from", "hypabase", "hypabase-memory"],
"env": { "HYPABASE_DB_PATH": "hypabase.db" }
}
}
}
uvx handles all Python dependencies automatically. Requires uv.
Store a memory — one verb, roles for the participants:
remember(penman='(prefers :subject Alice :object Python :memory_type semantic)')
Recall it:
recall(entity="Alice") # everything about Alice
recall(entity="Alice", action="assign", role="subject") # what Alice assigned
recall(entity=["Alice", "Bob"]) # memories involving both
recall(mood="planned") # all plans
Store a memory when the user:
Every memory is a verb with participants in role slots:
(verb :role "entity" :role "entity" ...)
Examples:
(prefers :subject Alice :object Python :memory_type semantic)
(assigned :subject Alice :object "billing task" :recipient Bob
:instrument Jira :locus Monday :tense past :memory_type episodic)
(has :subject "quick sort" :attribute "time complexity"
:value "O(n log n)" :memory_type semantic)
Multiple atoms in a single call:
(deployed :subject Alice :object API :locus Monday :tense past)
(reviewed :subject Bob :object API :locus Tuesday :tense past)
One action per memory. When a sentence contains multiple actions, decompose into separa...
这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。
# Hypabase Memory
Persistent memory for agents. Stores preferences, decisions, facts, and events as a connected knowledge graph. Recalled by who, what, when, or why.
## Setup
Add the MCP server to your OpenClaw config (`~/.openclaw/openclaw.json`):
```json
{
"mcpServers": {
"hypabase-memory": {
"command": "uvx",
"args": ["--from", "hypabase", "hypabase-memory"],
"env": { "HYPABASE_DB_PATH": "hypabase.db" }
}
}
}
```
`uvx` handles all Python dependencies automatically. Requires [uv](https://docs.astral.sh/uv/).
## Quick start
Store a memory — one verb, roles for the participants:
```
remember(penman='(prefers :subject Alice :object Python :memory_type semantic)')
```
Recall it:
```
recall(entity="Alice") # everything about Alice
recall(entity="Alice", action="assign", role="subject") # what Alice assigned
recall(entity=["Alice", "Bob"]) # memories involving both
recall(mood="planned") # all plans
```
## When to Remember
Store a memory when the user:
- Makes a decision or states a preference
- Shares a fact about themselves, their team, or a project
- Assigns a task or delegates work
- Describes an event, meeting, or outcome
- Explains a procedure or workflow
## PENMAN Notation
Every memory is a verb with participants in role slots:
```
(verb :role "entity" :role "entity" ...)
```
Examples:
```
(prefers :subject Alice :object Python :memory_type semantic)
(assigned :subject Alice :object "billing task" :recipient Bob
:instrument Jira :locus Monday :tense past :memory_type episodic)
(has :subject "quick sort" :attribute "time complexity"
:value "O(n log n)" :memory_type semantic)
```
Multiple atoms in a single call:
```
(deployed :subject Alice :object API :locus Monday :tense past)
(reviewed :subject Bob :object API :locus Tuesday :tense past)
```
**One action per memory.** When a sentence contains multiple actions, decompose into separa...Task Router
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