Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Context-Aware Delegation (SmartBeat)
Give isolated sessions (cron jobs, sub-agents, event handlers) full conversation context from your main session using sessions_history. Run cheap background...
skill openclawclawhub Free
Give isolated sessions (cron jobs, sub-agents, event handlers) full conversation context from your main session using sessions_history. Run cheap background...
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- README.md, SKILL.md, examples/morning-report-cron.json, examples/sub-agent-with-context.sh
Validation
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- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
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Agent handoff
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New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
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Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.2
Provenance
- Publisher
- RGBA-Research
- Source page
- View original listing
- Canonical URL
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Documentation
(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.
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
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: β Conversation history (what was discussed) β Memory files (persistent notes) β Cheap model (Haiku) β Full tool access
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
ApproachModelContextCost/RunWhen to UseMain sessionSonnetFull~$0.30Complex interactive workIsolated (blind)HaikuNone~$0.03Simple scheduled tasksContext-aware delegationHaikuFull~$0.03Background tasks needing context Savings: ~10x cheaper than main session, with same context awareness.
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: Sessions history: Recent interactive work 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: π WEATHER: [conditions] π OVERNIGHT: [from session history - what we worked on] π PERSISTENT NOTES: [from memory file] π§ EMAIL: [urgent only] π CALENDAR: [today's events] π 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)
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Docs1 Scripts1 Config
- SKILL.md
- README.md
- examples/sub-agent-with-context.sh
- examples/morning-report-cron.json