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phoenixclaw

Passive journaling skill that scans daily conversations via cron to generate markdown journals using semantic understanding. Use when: - User requests journaling ("Show me my journal", "What did I do today?") - User asks for pattern analysis ("Analyze my patterns", "How am I doing?") - User requests summaries ("Generate weekly/monthly summary")

Stars

0

Installs

0

Status

ACTIVE

Visibility

PUBLIC

安装方式

直接复制以下提示词,发送给你的 AI 助手即可完成安装。

请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 phoenixclaw 技能。 若已安装,则直接安装 phoenixclaw 技能。

Overview

Skill Key
goforu/phoenixclaw
Author
goforu
Source Repo
openclaw/skills
Version
-
Source Path
skills/goforu/phoenixclaw
Latest Commit SHA
c1266c8c396dbb18f80885c8bb5f328a5953769b

Extracted Content

SKILL.md excerpt

# PhoenixClaw: Zero-Tag Passive Journaling

PhoenixClaw automatically distills daily conversations into meaningful reflections using semantic intelligence.

Automatically identifies journal-worthy moments, patterns, and growth opportunities.

## 🛠️ Core Workflow

> [!critical] **MANDATORY: Complete Workflow Execution**
> This 9-step workflow MUST be executed in full regardless of invocation method:
> - **Cron execution** (10 PM nightly)
> - **Manual invocation** ("Show me my journal", "Generate today's journal", etc.)
> - **Regeneration requests** ("Regenerate my journal", "Update today's entry")
> 
> **Never skip steps.** Partial execution causes:
> - Missing images (session logs not scanned)
> - Missing finance data (Ledger plugin not triggered)
> - Incomplete journals (plugins not executed)

PhoenixClaw follows a structured pipeline to ensure consistency and depth:

1. **User Configuration:** Check for `~/.phoenixclaw/config.yaml`. If missing, initiate the onboarding flow defined in `references/user-config.md`.
2. **Context Retrieval:** 
   - **Scan memory files (NEW):** Read `memory/YYYY-MM-DD.md` and `memory/YYYY-MM-DD-*.md` files for manually recorded daily reflections. These files contain personal thoughts, emotions, and context that users explicitly ask the AI to remember via commands like "记一下" (remember this). **CRITICAL**: Do not skip these files - they contain explicit user reflections that session logs may miss.
   - **Scan session logs:** Call `memory_get` for the current day's memory, then **CRITICAL: Scan ALL raw session logs and filter by message timestamp**. Session files are often split across multiple files. Do NOT classify images by session file `mtime`:
      ```bash
      # Read all session logs from ALL known OpenClaw locations, then filter by per-message timestamp
      # Use timezone-aware epoch range to avoid UTC/local-day mismatches.
      TARGET_DAY="$(date +%Y-%m-%d)"
      TARGET_TZ="${TARGET_TZ:-Asia/Shanghai}"
      read START_EPO...

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