A comprehensive framework and configuration guide designed to prevent AI agents from freezing during large-scale batch operations by managing session transcript bloat.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install agent-batch-guard
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install agent-batch-guard using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Agent Batch Guard?
Agent Batch Guard is a specialized optimization skill designed to solve the critical issue of session transcript expansion within Openclaw Skills. When AI agents perform repetitive tasks such as bulk web scraping, multi-page app crawling, or historical data exports, the accumulation of tool call logs can cause session transcripts to swell to several megabytes. This results in compaction timeouts and silent agent failures where the system stops responding without error notifications.
By implementing this skill, developers provide agents with a multi-layered defense strategy. It shifts the heavy lifting from the conversation transcript into external scripts and structured file storage. This ensures that the agent's cognitive load remains manageable and the session remains stable, even during tasks involving hundreds of repetitive actions.
Agent Batch Guard Use Cases
- High-volume data scraping or multi-page app crawling where transcripts exceed 5MB.
- Automated scrolling and parsing tasks requiring more than 10-20 consecutive tool calls.
- Long-running historical data exports where task interruption and recovery are required.
- Scenarios where AI agents experience silent freezes or high latency due to compaction overhead.
How Agent Batch Guard Works
- The agent evaluates the task scale to determine if the operation requires direct conversation interaction or external scripting (tasks over 5 pages trigger scripting).
- A script-centric execution model is initiated where the agent generates a standalone Python or TypeScript script to handle repetitive loops internally.
- Raw data is strictly written to local files (e.g., data/scrape/) rather than being echoed back into the session transcript.
- The agent implements batch processing and breakpoint resumption, saving progress metadata after every batch to allow for recovery.
- Platform-level optimizations such as Context Pruning TTL and rolling compaction modes are applied to maintain a lean memory footprint.
Agent Batch Guard Setup
To integrate Agent Batch Guard into your Openclaw Skills workflow, update your agent behavior guidelines and environment configurations.
# Create a dedicated directory for batch data storage
mkdir -p data/scrape/
# Link the protection guidelines to your agent's workspace
# This ensures the agent is aware of session bloat constraints
cat ~/.openclaw/skills/agent-batch-guard/SKILL.md >> AGENTS.md
Configure your openclaw.json to optimize context handling:
{
"agents": {
"defaults": {
"contextPruning": {
"mode": "cache-ttl",
"ttl": "30m"
},
"timeoutSeconds": 900
}
}
}
Agent Batch Guard Data Schema & Taxonomy
The skill organizes batch data and state tracking using a structured filesystem approach to keep the transcript clean:
| Path | Purpose | Format |
|---|---|---|
data/scrape/batch_*.json |
Segmented data storage to prevent memory overflow | JSON |
data/scrape/progress.json |
Tracking current page, total items, and last successful run | JSON |
data/scrape/orders_summary.json |
The final consolidated report generated for the user | JSON |
/tmp/executor_script.py |
Temporary scripts generated by the agent for internal looping | Python |
Agent Batch Guard Advanced Features
- Adaptive Scheduling: Dynamically adjusts concurrency limits based on system latency and success rates.
- Circuit Breakers: Automatically pauses tasks after a threshold of consecutive failures (e.g., 5 failures) to prevent resource waste.
- Sub-agent Isolation: Offloads heavy processing to child agents with independent transcripts to protect the primary session.
- Exponential Backoff: Implements intelligent retry logic for transient network or rate-limiting errors encountered during batch runs.
SKILL.md
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