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OpenClaw

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")

goforu0 source installs☆ 0 Repository stars

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

SkillHub CLI

skillhub install goforu/phoenixclaw

Inspect the source and compatibility requirements, then follow its installation steps.

Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.

View source ↗Guides

Skill instructions

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:
      # 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...
      

Source information

Source
github
Repository
openclaw/skills
Path
skills/goforu/phoenixclaw
Version
—
Commit
c1266c8c396dbb18f80885c8bb5f328a5953769b
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

Extracted content

SKILL.md
# 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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