Token导航 LogoToken导航TokenDH.com
研究检索external-serviceclawhub未标认证来源可访问clear审计提醒

fpms-memory内存

Agent Skill

fpms-memory 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

3,128

周安装

133

GitHub Stars

公开资料未说明

下载量

1,096
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:fpms-memory(内存)
来源仓库:https://github.com/jeff0052/fpms-memory
安装命令:
openclaw skills install fpms-memory
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install fpms-memory

简介

认知记忆引擎 — 为您的人工智能提供持久的工作跟踪、主动风险警报和交叉对话连续性。再也不会失去对项目的跟踪。

SKILL.md

name
fpms-memory
description
Cognitive memory engine — gives your AI persistent work tracking, proactive risk alerts, and cross-conversation continuity. Never lose track of projects again.
version
0.2.0
metadata
openclaw
emoji
🧠
homepage
https://github.com/jeff0052/founderOSclaudecode
requires
bins
install
package
focalpoint
bins
[focalpoint]

FPMS — Focal Point Memory System

Your AI forgets everything between conversations. FPMS fixes that.

Not just memory — attention management. FPMS tracks your projects, detects stuck tasks, and loads the right context at the right time.

What You Get

  • Cross-conversation memory — Start Monday, continue Wednesday, review Friday
  • Structured work tracking — Projects → Tasks → Subtasks with status lifecycle
  • Proactive alerts — "Task X has been blocked for 3 days"
  • Smart context loading — Only loads what fits your token budget
  • GitHub sync — Issues auto-sync as FPMS nodes

How It's Different From Other Memory Tools

| | Mem0/Zep | FPMS | |--|---------|----------| | Remembers conversations | Yes | Yes (via prompt rules) | | Tracks tasks & projects | No | Yes | | Alerts you about stuck work | No | Yes (heartbeat) | | Manages token budget | No | Yes (L0/L1/L2) | | Parent-child task hierarchy | No | Yes | | GitHub integration | No | Yes |

Other tools remember what was said. FPMS manages what needs to be done.

Setup

1. Install

pip install focalpoint

2. Add MCP server to openclaw.yaml

mcp_servers:
  fpms:
    command: focalpoint

3. Restart OpenClaw

That's it. 18 tools are now available in your conversations.

Use Cases

Project tracking

You: "Create a project for the product launch with 3 tasks"
(Next day)
You: "What's the launch status?"
AI:  "3 tasks: 1 done, 1 active, 1 blocked. The blocked task
      is waiting on design review — it's been 2 days."

Decision memory

You: "We're going with Stripe for payments"
(Two weeks later)
You: "Why did we pick Stripe?"
AI:  "You decided on March 15 — better API and lower international fees."

Risk detection

AI automatically runs heartbeat and finds:
  - Deploy task BLOCKED for 4 days
  - Docs update STALE — no activity for a week
  - Bug fix AT RISK — deadline is tomorrow

Available Tools (18)

ToolWhat it does
bootstrapLoad memory context (call at conversation start)
heartbeatScan for risks: blocked, stale, at-risk tasks
create_nodeCreate a project/task/goal
update_statusChange status (inbox/active/waiting/done/dropped)
append_logRecord decisions, progress, links
get_context_bundleGet token-budgeted context payload
search_nodesFind tasks by status, parent, source
get_nodeGet full details of a work item
shift_focusSwitch AI attention to a specific task
expand_contextSee parent, children, dependencies
update_fieldUpdate title, summary, deadline, etc.
attach_node / detach_nodeMove tasks in hierarchy
add_dependency / remove_dependencyManage task dependencies
unarchiveRestore completed/dropped tasks
set_persistentProtect tasks from auto-archive
get_assembly_traceDebug context assembly

Automatic Memory Rules

Follow these rules in EVERY conversation:

  1. Conversation start → Call bootstrap to load memory
  2. User mentions a task/project/goalcreate_node
  3. User makes a decisionappend_log to the relevant node
  4. Task progressesupdate_status
  5. Before conversation endsappend_log key takeaways
  6. Every ~10 minheartbeat to check for risks

Requirements

  • Python 3.10+
  • No external services — runs 100% locally on SQLite

Links

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

77.35%
按下载量换算848

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills