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BytesAgain β€Ί Skills β€Ί Context-Aware Delegation (SmartBeat)
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Context-Aware Delegation (SmartBeat)

by @rgba-research

Give isolated sessions (cron jobs, sub-agents, event handlers) full conversation context from your main session using sessions_history. Run cheap background...

Versionv1.0.2
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#writing#legal#education#automation
TERMINAL
clawhub install context-aware-delegation

πŸ“– About This Skill

name: context-aware-delegation description: Give isolated sessions (cron jobs, sub-agents, event handlers) full conversation context from your main session using sessions_history. Run cheap background tasks (Haiku) with expensive context (Sonnet-level awareness) β€” best of both worlds. homepage: https://gitlab.com/rgba_research/context-aware-delegation author: RGBA Research metadata: { "openclaw": { "emoji": "πŸ”—", "requires": { "tools": ["sessions_list", "sessions_history"] }, }, }

Context-Aware Delegation

(aka "SmartBeat")

Problem: Isolated sessions (cron jobs, sub-agents) can't see your main session conversation history. They're cheap (use Haiku) but blind to context.

Solution: Use sessions_history to give isolated sessions full awareness of what happened in your main chat β€” at a fraction of the cost of running everything in main session.

Quick Start

Morning Report Example

You want a daily report that includes "what we accomplished last night" β€” but running that in main session with Sonnet costs ~$0.30/report. Using an isolated session with Haiku costs ~$0.03, but can't see conversation history.

Solution: Isolated session queries main session history first.

// Inside your cron payload.message:
"1. Query main session history: sessions_history('agent:main:telegram:direct:{userId}', limit=50)
2. Read memory files: memory/YYYY-MM-DD.md
3. Fetch weather for Austin 78721
4. Generate report combining:
   - Recent conversation highlights
   - Memory file summaries
   - Current conditions
5. Send via Telegram + email"

Cost: ~$0.03 with Haiku (10x cheaper than Sonnet main session) Context: Full awareness of overnight work

Pattern Overview

1. Identify Main Session Key

# List sessions to find main
sessions_list(limit=10)

Typical main session key format:


agent:main:telegram:direct:{userId}


agent:main:main

2. Query History from Isolated Session

// In cron job, sub-agent, or event handler:
sessions_history({
  sessionKey: "agent:main:telegram:direct:8264585335",
  limit: 50  // Last 50 messages
})

Returns conversation history even though you're in an isolated session.

3. Use Context + Execute Task

Your isolated session now has:

  • βœ… Conversation history (what was discussed)
  • βœ… Memory files (persistent notes)
  • βœ… Cheap model (Haiku)
  • βœ… Full tool access

    • Use Cases

    Cron Jobs with Context

    Morning reports: 

    Schedule: 8 AM daily
Model: Haiku (~$0.03/run)
Task: Read overnight work, check email, send summary
Context: Last 50 messages from main session

    End-of-day summaries: 

    Schedule: 9 PM daily
Model: Haiku
Task: What got done today? What's pending?
Context: Today's full conversation

    Periodic check-ins: 

    Schedule: Every 2 hours (9 AM - 9 PM)
Model: Haiku
Task: Anything urgent in email/calendar?
Context: Recent discussion about priorities

    Sub-Agent Delegation

    Background builds: 

    sessions_spawn({
  task: "Build the AREF product page based on our discussion",
  model: "haiku",
  // In the task prompt:
  // "First, query main session history to see our conversation about AREF requirements..."
})

    Research tasks: 

    sessions_spawn({
  task: "Research Unreal Engine integration patterns. Reference our earlier discussion about AREF goals.",
  model: "haiku"
})

    Event-Driven Handlers

    Webhook arrives β†’ isolated session handles it: 

    // Webhook payload triggers isolated session
// Session logic:
"1. Query main session to see: what did J and I agree about this client?
2. Process webhook based on that context
3. Take action or notify"

    Cost Comparison

    | Approach | Model | Context | Cost/Run | When to Use | |----------|-------|---------|----------|-------------| | Main session | Sonnet | Full | ~$0.30 | Complex interactive work | | Isolated (blind) | Haiku | None | ~$0.03 | Simple scheduled tasks | | Context-aware delegation | Haiku | Full | ~$0.03 | Background tasks needing context |

    Savings: ~10x cheaper than main session, with same context awareness.

    Implementation Tips

    Finding Your Main Session Key

    sessions_list({ kinds: ["main"], limit: 5 })
// Or:
sessions_list({ limit: 10 })
// Look for: agent:main:telegram:direct:{yourUserId}

    How Much History?

  • 10 messages: Just recent context (~2KB)
  • 50 messages: Last few hours of work (~10KB)
  • 100 messages: Full day or multi-session context (~20KB)

    • Start with 50, adjust based on needs.

    Combining History + Memory

    Best results come from: 1. Sessions history: Recent interactive work 2. Memory files: Persistent decisions/notes

    "1. sessions_history(limit=30) β†’ what we discussed today
2. read memory/2026-02-13.md β†’ decisions logged
3. Combine both sources for complete picture"

    Morning Report Recipe

    Complete example for daily morning report:

    Cron Job Setup: 

    {
  schedule: { kind: "cron", expr: "0 8 * * *", tz: "America/Chicago" },
  sessionTarget: "isolated",
  payload: {
    kind: "agentTurn",
    model: "haiku",
    message: Generate morning report:
    1. Query main session: sessions_history('agent:main:telegram:direct:8264585335', limit=50)
2. Read yesterday's memory: memory/YYYY-MM-DD.md
3. Get weather: Austin 78721
4. Check email (gog or himalaya)
5. Check calendar events for today
    Report format:
πŸ“ WEATHER: [conditions]
πŸŒ™ OVERNIGHT: [from session history - what we worked on]
πŸ“ PERSISTENT NOTES: [from memory file]
πŸ“§ EMAIL: [urgent only]
πŸ“… CALENDAR: [today's events]
πŸ”— DASHBOARD: [mission control link]
    Send to Telegram using message tool.
    Note: Email delivery from isolated sessions requires SMTP credentials or is better handled via main session heartbeats for reliability.
  },
  delivery: { mode: "announce", to: "8264585335", channel: "telegram" }
}

    Cost: ~$0.03/report (~$1/month) Context: Full overnight work awareness Timing: Exact (8 AM every day)

    Limitations

    History truncation:

  • sessions_history returns limited content (typically last N messages)
  • Very long messages may be truncated
  • For deep archives, rely on memory files

    • Main session must exist:

  • If main session is brand new (no messages), history is empty
  • Isolated sessions can't create main session history, only read it

    • Not real-time:

  • History reflects state when queried
  • If main session is actively running, very latest messages might not appear immediately

    • Best Practices

    1. Write good memory summaries Even with session history access, persistent memory files are gold. Don't rely solely on conversation history.

    2. Query only what you need limit=10 for quick context, limit=50 for substantial work, limit=100 for deep dives.

    3. Chain tools effectively 

    sessions_history β†’ memory_get β†’ web_search β†’ message
    Context first, then action.

    4. Use Haiku for delegation, Sonnet for decisions

  • Isolated background work: Haiku
  • Interactive problem-solving: Sonnet
  • Morning reports/summaries: Haiku
  • Architecture discussions: Sonnet

    • Troubleshooting

    "Empty session history"

  • Check session key is correct: sessions_list()
  • Main session might be new (no messages yet)
  • Use limit parameter

    • "Content truncated"

  • Reduce limit (fewer messages = more complete content)
  • Rely on memory files for archival data

    • "Isolated session can't send messages"

  • Use message tool, not sessions_send
  • Ensure delivery.mode is set in cron config OR use message tool directly

    • Related Patterns

  • Heartbeats: Main session periodic checks (full context, main model)
  • Sub-agents: Long-running background tasks
  • Cron jobs: Scheduled isolated work
  • Memory files: Persistent cross-session storage

    • Credits

    Discovered by RGBA Research during OpenClaw optimization work. Published to ClawHub as open pattern for the community.

    Contact: https://rgbaresearch.com License: MIT (free to use, adapt, share)

    ⚑ When to Use

    TriggerAction
    **Morning reports:**
    ```bash
    Schedule: 8 AM daily
    Model: Haiku (~$0.03/run)
    Task: Read overnight work, check email, send summary
    Context: Last 50 messages from main session
    ```
    **End-of-day summaries:**
    ```bash
    Schedule: 9 PM daily
    Model: Haiku
    Task: What got done today? What's pending?
    Context: Today's full conversation
    ```
    **Periodic check-ins:**
    ```bash
    Schedule: Every 2 hours (9 AM - 9 PM)
    Model: Haiku
    Task: Anything urgent in email/calendar?
    Context: Recent discussion about priorities
    ```
    ### Sub-Agent Delegation
    **Background builds:**
    ```javascript
    sessions_spawn({
    task: "Build the AREF product page based on our discussion",
    model: "haiku",
    // In the task prompt:
    // "First, query main session history to see our conversation about AREF requirements..."
    })
    ```
    **Research tasks:**
    ```javascript
    sessions_spawn({
    task: "Research Unreal Engine integration patterns. Reference our earlier discussion about AREF goals.",
    model: "haiku"
    })
    ```
    ### Event-Driven Handlers
    **Webhook arrives β†’ isolated session handles it:**
    ```javascript
    // Webhook payload triggers isolated session
    // Session logic:
    "1. Query main session to see: what did J and I agree about this client?
    2. Process webhook based on that context
    3. Take action or notify"
    ```

    πŸ’‘ Examples

    Morning Report Example

    You want a daily report that includes "what we accomplished last night" β€” but running that in main session with Sonnet costs ~$0.30/report. Using an isolated session with Haiku costs ~$0.03, but can't see conversation history.

    Solution: Isolated session queries main session history first.

    // Inside your cron payload.message:
"1. Query main session history: sessions_history('agent:main:telegram:direct:{userId}', limit=50)
2. Read memory files: memory/YYYY-MM-DD.md
3. Fetch weather for Austin 78721
4. Generate report combining:
   - Recent conversation highlights
   - Memory file summaries
   - Current conditions
5. Send via Telegram + email"

    Cost: ~$0.03 with Haiku (10x cheaper than Sonnet main session) Context: Full awareness of overnight work

    πŸ“‹ Tips & Best Practices

    1. Write good memory summaries Even with session history access, persistent memory files are gold. Don't rely solely on conversation history.

    2. Query only what you need limit=10 for quick context, limit=50 for substantial work, limit=100 for deep dives.

    3. Chain tools effectively 

    sessions_history β†’ memory_get β†’ web_search β†’ message
    Context first, then action.

    4. Use Haiku for delegation, Sonnet for decisions

  • Isolated background work: Haiku
  • Interactive problem-solving: Sonnet
  • Morning reports/summaries: Haiku
  • Architecture discussions: Sonnet