phoenixclaw

Security

Passive journaling skill that scans daily conversations from ALL session paths (main, agents, cron) 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")

Install

openclaw skills install phoenixclaw

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:

User Configuration: Check for ~/.phoenixclaw/config.yaml. If missing, initiate the onboarding flow defined in references/user-config.md.
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_EPOCH END_EPOCH < <(
  python3 - <<'PY' "$TARGET_DAY" "$TARGET_TZ"
```

from datetime import datetime, timedelta from zoneinfo import ZoneInfo import sys

day, tz = sys.argv[1], sys.argv[2] start = datetime.strptime(day, "%Y-%m-%d").replace(tzinfo=ZoneInfo(tz)) end = start + timedelta(days=1) print(int(start.timestamp()), int(end.timestamp())) PY )

  # Recursively scan all session directories (multi-agent architecture support)
  for dir in "$HOME/.openclaw/sessions" \
             "$HOME/.openclaw/agents" \
             "$HOME/.openclaw/cron/runs" \
             "$HOME/.agent/sessions"; do
    [ -d "$dir" ] || continue
    find "$dir" -type f -name "*.jsonl" -print0
  done |
    xargs -0 jq -cr --argjson start "$START_EPOCH" --argjson end "$END_EPOCH" '
      (.timestamp // .created_at // empty) as $ts
      | ($ts | split(".")[0] + "Z" | fromdateiso8601?) as $epoch
      | select($epoch != null and $epoch >= $start and $epoch < $end)
    '
  ```
  Read **all matching files** regardless of their numeric naming (e.g., file_22, file_23 may be earlier in name but still contain today's messages).
- **EXTRACT IMAGES FROM SESSION LOGS**: Session logs contain `type: "image"` entries with file paths. You MUST:
  1. Find all image entries (e.g., `"type":"image"`)
  2. Keep only entries where message `timestamp` is in the target date range
  3. Extract the `file_path` or `url` fields
  4. Copy files into `assets/YYYY-MM-DD/`
  5. Rename with descriptive names when possible
- **Why session logs are mandatory**: `memory_get` returns **text only**. Image metadata, photo references, and media attachments are **only available in session logs**. Skipping session logs = missing all photos.
- **Activity signal quality**: Do not treat heartbeat/cron system noise as user activity. Extract user/assistant conversational content and media events first, then classify moments.
- **FILTER HEARTBEAT MESSAGES (CRITICAL)**: Session logs contain system heartbeat messages that MUST be excluded from journaling. When scanning messages, SKIP any message matching these criteria:
  1. **User heartbeat prompts**: Messages containing "Read HEARTBEAT.md" AND "reply HEARTBEAT_OK"
  2. **Assistant heartbeat responses**: Messages containing ONLY "HEARTBEAT_OK" (with optional leading/trailing whitespace)
  3. **Cron system messages**: Messages with role "system" or "cron" containing job execution summaries (e.g., "Cron job completed", "A cron job")
  
  Example jq filter to exclude heartbeats:
  ```jq
  # Exclude heartbeat messages
  | select(
      (.message.content? | type == "array" and 
        (.message.content | map(.text?) | join("") | 
          test("Read HEARTBEAT\.md"; "i") | not))
      and
      (.message.content? | type == "array" and 
        (.message.content | map(.text?) | join("") | 
          test("^\\s*HEARTBEAT_OK\\s*$"; "i") | not))
    )
  ```
- **Edge case - Midnight boundary**: For late-night activity that spans midnight, expand the **timestamp** range to include spillover windows (for example, previous day 23:00-24:00) and still filter per-message by `timestamp`.

Merge sources: Combine content from both memory files and session logs. Memory files capture explicit user reflections; session logs capture conversational flow and media. Use both to build complete context.
Fallback: If memory is sparse, reconstruct context from session logs, then update memory so future runs use the enriched memory. Incorporate historical context via memory_search (skip if embeddings unavailable)

Moment Identification: Identify "journal-worthy" content: critical decisions, emotional shifts, milestones, or shared media. See references/media-handling.md for photo processing. This step generates the moments data structure that plugins depend on. Image Processing (CRITICAL):
- For each extracted image, generate descriptive alt-text via Vision Analysis
- Categorize images (food, selfie, screenshot, document, etc.)
Filter Finance Screenshots (NEW): Payment screenshots (WeChat Pay, Alipay, etc.) should NOT be included in the journal narrative. These are tool images, not life moments.

Detection criteria (check any):
1. OCR keywords: "支付成功", "支付完成", "微信支付", "支付宝", "订单号", "交易单号", "¥" + amount
2. Context clues: Image sent with nearby text containing "记账", "支付", "付款", "转账"
3. Visual patterns: Standard payment app UI layouts (green WeChat, blue Alipay)
Handling rules:
- Mark as finance_screenshot type
- Route to Ledger plugin (if enabled) for transaction recording
- EXCLUDE from journal main narrative unless explicitly described as part of a life moment (e.g., "今天请朋友吃饭" with payment screenshot)
- Never include raw payment screenshots in daily journal images section
- Match images to moments (e.g., breakfast photo → breakfast moment)
- Store image metadata with moments for journal embedding
Pattern Recognition: Detect recurring themes, mood fluctuations, and energy levels. Map these to growth opportunities using references/skill-recommendations.md.
Plugin Execution: Execute all registered plugins at their declared hook points. See references/plugin-protocol.md for the complete plugin lifecycle:
- pre-analysis → before conversation analysis
- post-moment-analysis → Ledger and other primary plugins execute here
- post-pattern-analysis → after patterns detected
- journal-generation → plugins inject custom sections
- post-journal → after journal complete
Journal Generation: Synthesize the day's events into a beautiful Markdown file using assets/daily-template.md. Follow the visual guidelines in references/visual-design.md. Include all plugin-generated sections at their declared section_order positions.
- Embed curated images only, not every image. Prioritize highlights and moments.
- Route finance screenshots to Ledger sections (receipts, invoices, transaction proofs).
- Use Obsidian format from references/media-handling.md with descriptive captions.
- Generate image links from filesystem truth: compute the image path relative to the current journal file directory. Never output absolute paths.
- Do not hardcode path depth (../ or ../../): calculate dynamically from daily_file_path and image_path.
- Use copied filename as source of truth: if asset file is image_124917_2.jpg, the link must reference that exact filename.
Timeline Integration: If significant events occurred, append them to the master index in timeline.md using the format from assets/timeline-template.md and references/obsidian-format.md.
Growth Mapping: Update growth-map.md (based on assets/growth-map-template.md) if new behavioral patterns or skill interests are detected.
Profile Evolution: Update the long-term user profile (profile.md) to reflect the latest observations on values, goals, and personality traits. See references/profile-evolution.md and assets/profile-template.md.

⏰ Cron & Passive Operation

PhoenixClaw is designed to run without user intervention. It utilizes OpenClaw's built-in cron system to trigger its analysis daily at 10:00 PM local time (0 22 * * *).

Setup details can be found in references/cron-setup.md.
Mode: Primarily Passive. The AI proactively summarizes the day's activities without being asked.

Rolling Journal Window (NEW)

To solve the 22:00-24:00 content loss issue, PhoenixClaw now supports a rolling journal window mechanism:

Problem: Fixed 24-hour window (00:00-22:00) misses content between 22:00-24:00 when journal is generated at 22:00.

Solution: scripts/rolling-journal.js scans from last journal time → now instead of fixed daily boundaries.

Features:

Configurable schedule hour (default: 22:00, customizable via ~/.phoenixclaw/config.yaml)
Rolling window: No content loss even if generation time varies
Backward compatible with existing late-night-supplement.js

Configuration (~/.phoenixclaw/config.yaml):

schedule:
  hour: 22        # Journal generation time
  minute: 0
  rolling_window: true   # Enable rolling window (recommended)

Usage:

# Default: generate from last journal to now
node scripts/rolling-journal.js

# Specific date
node scripts/rolling-journal.js 2026-02-12

💬 Explicit Triggers

While passive by design, users can interact with PhoenixClaw directly using these phrases:

"Show me my journal for today/yesterday."
"What did I accomplish today?"
"Analyze my mood patterns over the last week."
"Generate my weekly/monthly summary."
"How am I doing on my personal goals?"
"Regenerate my journal." / "重新生成日记"

[!warning] Manual Invocation = Full Pipeline When users request journal generation/regeneration, you MUST execute the complete 9-step Core Workflow above. This ensures:

Photos are included (via session log scanning)

Ledger plugin runs (via post-moment-analysis hook)

All plugins execute (at their respective hook points)

Common mistakes to avoid:

❌ Only calling memory_get (misses photos)

❌ Skipping moment identification (plugins never trigger)

❌ Generating journal directly without plugin sections

📚 Documentation Reference

References (`references/`)

user-config.md: Initial onboarding and persistence settings.
cron-setup.md: Technical configuration for nightly automation.
plugin-protocol.md: Plugin architecture, hook points, and integration protocol.
media-handling.md: Strategies for extracting meaning from photos and rich media.
session-day-audit.js: Diagnostic utility for verifying target-day message coverage across session logs.
visual-design.md: Layout principles for readability and aesthetics.
obsidian-format.md: Ensuring compatibility with Obsidian and other PKM tools.
profile-evolution.md: How the system maintains a long-term user identity.
skill-recommendations.md: Logic for suggesting new skills based on journal insights.

Assets (`assets/`)

daily-template.md: The blueprint for daily journal entries.
weekly-template.md: The blueprint for high-level weekly summaries.
profile-template.md: Structure for the profile.md persistent identity file.
timeline-template.md: Structure for the timeline.md chronological index.
growth-map-template.md: Structure for the growth-map.md thematic index.