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User Growth Coach
by
Jack-Yang-ai
· GitHub ↗
· v2.3.1
· MIT-0
311
Downloads
0
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1
Active Installs
3
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Install in OpenClaw
/install user-growth-coach
Description
三层反馈复盘系统 + 随手记，连接当前输入、历史复盘和日常上下文，自动识别深层行为模式。
Usage Guidance
This skill is coherent with its purpose, but it will read your local OpenClaw session transcripts (by default ~/.openclaw/agents/main/sessions) and write structured files under your workspace (default ~/.openclaw/workspace/memory/...). Before installing/run: 1) confirm the session and digest directory paths in SKILL.md/README and, if desired, set OPENCLAW_SESSIONS_DIR / OPENCLAW_DIGEST_DIR to safer locations; 2) back up any existing markdown memory files — migrate-md-to-jsonl.py renames the source file to .bak; 3) review the scripts (they are local and not networked) and test them on a copy of your data to ensure they behave as you expect; 4) if you do not want the skill to process all session transcripts (which may contain sensitive chats), restrict the sessions directory or run extraction scripts manually rather than via an automated cron.
Capability Analysis
Type: OpenClaw Skill
Name: user-growth-coach
Version: 2.3.1
The 'User Growth Coach' skill bundle is a productivity tool designed to analyze user behavior and provide feedback based on session history and manual entries. While the scripts 'extract-raw-inputs.py' and 'extract-daily-digest.py' access sensitive session transcripts located in the OpenClaw sessions directory, this behavior is explicitly documented and necessary for the 'L3' contextual feedback feature. The analysis found no evidence of data exfiltration, unauthorized network access, obfuscation, or malicious command execution; all data processing remains local to the user's environment.
Capability Assessment
Purpose & Capability
The skill claims to implement a three-layer capture/review system and includes scripts and runtime instructions to: capture quick notes, read past JSONL/markdown records, and generate a daily digest from agent session transcripts. The files and scripts present (extract-raw-inputs.py, extract-daily-digest.py, migrate-md-to-jsonl.py, trigger-router.js) match that purpose.
Instruction Scope
SKILL.md instructs the agent to read session transcripts and local memory files (memory/user-growth/* and memory/daily-digest/*) and to run the included scripts to generate digests. Reading transcripts is necessary for L3/day-digest functionality, but it means the skill will process potentially sensitive conversation contents from the agent's sessions directory.
Install Mechanism
No install spec is provided (instruction-only with shipped scripts). That is lower risk: nothing is fetched from the network or installed automatically. The code is included in the bundle and will run locally if invoked.
Credentials
The registry metadata lists no required env vars, but the README/SKILL.md reference optional env vars (OPENCLAW_SESSIONS_DIR and OPENCLAW_DIGEST_DIR) to point at session and digest directories. No secrets or external API keys are requested. The environment access requested is proportional to the stated functionality, though the metadata omission is a minor inconsistency.
Persistence & Privilege
The scripts create and write files under the user's workspace (memory/daily-digest/*.md, memory/user-growth/*.jsonl). migrate-md-to-jsonl.py renames (moves) the input markdown to a .bak backup — i.e., it modifies user files. This file-write and rename behavior is expected for storing digests and migrations but is a material side effect the user should be aware of before running.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install user-growth-coach - After installation, invoke the skill by name or use
/user-growth-coach - Provide required inputs per the skill's parameter spec and get structured output
Version History
v2.3.1
v2.3.1 修复元数据字段问题
v2.3.0
Version 2.3.0
- 新增「随手记（Capture）」模式：支持用户白天随时捕获灵感、决定、观察等，零负担，无需深度分析。
- 增加多种「随手记」触发词及自动分类打标签，并极简确认归档。
- 复盘时自动整合当天随手记，输出「今日随手记回顾」并作为L2分析素材。
- 存储结构优化，新增 captures-YYYY-MM.jsonl 文件用于随手记记录。
- 汇总与复盘时可统计随手记分布及与复盘的关联，追踪决策后续执行情况。
- 原有三层（L1/L2/L3）复盘协议及日常摘要流程保持不变。
v2.2.0
User Growth Coach v2.2 introduces a powerful three-layer feedback review system for identifying deep behavioral patterns.
- 全新三层反馈架构：L1（当前输入反馈）、L2（历史行为模式洞察）、L3（日常上下文深度关联）
- 支持多种模式（快速/标准/深度），灵活触发与反馈粒度
- 引入自动行为模式洞察，输出动机解析与具体行动处方
- 日常交互摘要（daily-digest）自动提取与结构化总结，深度补充复盘数据
- 新增成长/复盘汇总输出：跨天模式追踪、承诺清单、建议与明日关注点
- 精细化数据与存储结构，支持高质量推理模型路由
Metadata
Frequently Asked Questions
What is User Growth Coach?
三层反馈复盘系统 + 随手记，连接当前输入、历史复盘和日常上下文，自动识别深层行为模式。 It is an AI Agent Skill for Claude Code / OpenClaw, with 311 downloads so far.
How do I install User Growth Coach?
Run "/install user-growth-coach" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is User Growth Coach free?
Yes, User Growth Coach is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does User Growth Coach support?
User Growth Coach is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created User Growth Coach?
It is built and maintained by Jack-Yang-ai (@jack-yang-ai); the current version is v2.3.1.
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