Skill: jeff0052/fpms-memory (version 0.2.0)

--- 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: - python3 install: - kind: uv 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 ```bash pip install focalpoint ``` ### 2. Add MCP server to openclaw.yaml ```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) | Tool | What it does | |------|-------------| | `bootstrap` | Load memory context (call at conversation start) | | `heartbeat` | Scan for risks: blocked, stale, at-risk tasks | | `create_node` | Create a project/task/goal | | `update_status` | Change status (inbox/active/waiting/done/dropped) | | `append_log` | Record decisions, progress, links | | `get_context_bundle` | Get token-budgeted context payload | | `search_nodes` | Find tasks by status, parent, source | | `get_node` | Get full details of a work item | | `shift_focus` | Switch AI attention to a specific task | | `expand_context` | See parent, children, dependencies | | `update_field` | Update title, summary, deadline, etc. | | `attach_node` / `detach_node` | Move tasks in hierarchy | | `add_dependency` / `remove_dependency` | Manage task dependencies | | `unarchive` | Restore completed/dropped tasks | | `set_persistent` | Protect tasks from auto-archive | | `get_assembly_trace` | Debug 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/goal** → `create_node` 3. **User makes a decision** → `append_log` to the relevant node 4. **Task progresses** → `update_status` 5. **Before conversation ends** → `append_log` key takeaways 6. **Every ~10 min** → `heartbeat` to check for risks ## Requirements - Python 3.10+ - No external services — runs 100% locally on SQLite ## Links - [GitHub](https://github.com/jeff0052/founderOSclaudecode) - [PyPI](https://pypi.org/project/fpms/) - [Full Documentation](https://github.com/jeff0052/founderOSclaudecode/blob/main/docs/USAGE-GUIDE.md)


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)