openclaw - 💡(How to fix) Fix [Proposal] Agent Autonomy Patterns — Undo Stacks & Atomic Operations [1 comments, 2 participants]

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openclaw/openclaw#50928Fetched 2026-04-08 01:06:31
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Error Message

  • After any tool failure, analyze error; if unknown pattern, log to learnings.md with suggested fix.
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Proposal: Agent Autonomy Patterns — Undo Stacks & Atomic Operations

Vision (2025 AI agents): Treat atomicity as infrastructure, not prompting. Enable reversible operations and self-improvement loops.

Undo Stack:

  • Wrap state-changing operations in with undo_context(): block.
  • Push inverse operation onto thread-local stack before executing.
  • On failure or explicit undo, pop and execute inverse (e.g., edit → restore oldText; file write → backup then restore; gh pr create → close PR).
  • Record undo history in memory/undo-log-YYYY-MM-DD.md for audit.

Atomic Operations:

  • Encapsulate complex multi-step workflows as single atomic units with all-or-nothing semantics.
  • Use two-phase commit pattern: preparecommit or rollback.
  • Example: GitHub issue creation + label assignment + comment → if any step fails, rollback previous steps.

Self-Improvement Loops:

  • After any tool failure, analyze error; if unknown pattern, log to learnings.md with suggested fix.
  • Periodically review learnings.md and propose code changes or documentation updates.
  • Confidence scoring on outputs: attach confidence: high/medium/low based on evidence count; trigger deeper research automatically for low-confidence.

Implementation plan:

  1. Design undo API: push_undo(inverse_callable); execute_undo().
  2. Wrap all memory and write operations with undo support.
  3. Wrap external API calls (gh, exec with side effects) with undo where possible.
  4. Add --dry-run flag to simulate operations and show undo plan.
  5. Daily job: scan undo-log for long-lived reversals; notify if stuck.

Related: #41960 (ToolResultCompactor) — ensure compactor preserves undo metadata.

extent analysis

Fix Plan

To implement the proposed Agent Autonomy Patterns, we will focus on the following steps:

  • Implementing the undo API
  • Wrapping state-changing operations with undo support
  • Adding atomic operations with two-phase commit pattern
  • Implementing self-improvement loops

Implementation Steps

Undo API

class UndoContext:
    def __init__(self):
        self.undo_stack = []

    def push_undo(self, inverse_callable):
        self.undo_stack.append(inverse_callable)

    def execute_undo(self):
        if self.undo_stack:
            inverse_callable = self.undo_stack.pop()
            inverse_callable()

# Example usage:
undo_context = UndoContext()

def edit_text(old_text, new_text):
    def inverse_edit():
        # Restore old text
        print(f"Restoring old text: {old_text}")

    undo_context.push_undo(inverse_edit)
    # Execute edit operation
    print(f"Editing text: {new_text}")

edit_text("old text", "new text")
undo_context.execute_undo()

Atomic Operations

class AtomicOperation:
    def __init__(self):
        self.prepared = False

    def prepare(self):
        # Prepare operation (e.g., create GitHub issue)
        self.prepared = True

    def commit(self):
        # Commit operation (e.g., assign label and comment)
        if self.prepared:
            print("Operation committed")
        else:
            print("Operation not prepared")

    def rollback(self):
        # Rollback operation (e.g., close GitHub issue)
        if self.prepared:
            print("Operation rolled back")
        else:
            print("Operation not prepared")

# Example usage:
atomic_operation = AtomicOperation()
atomic_operation.prepare()
atomic_operation.commit()

Self-Improvement Loops

def analyze_error(error):
    # Analyze error and log to learnings.md if unknown pattern
    print(f"Analyzing error: {error}")

def review_learnings():
    # Periodically review learnings.md and propose code changes or documentation updates
    print("Reviewing learnings")

# Example usage:
analyze_error("unknown error")
review_learnings()

Verification

To verify the implementation, test the undo API, atomic operations, and self-improvement loops with various scenarios, including:

  • Successful operations with undo support
  • Failed operations with rollback
  • Self-improvement loops with error analysis and learnings review

Extra Tips

  • Ensure that the undo API and atomic operations are properly integrated with the existing codebase.
  • Use logging and monitoring to track the performance and effectiveness of the self-improvement loops.
  • Regularly review and update the learnings.md file to ensure that the system is continuously improving.

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openclaw - 💡(How to fix) Fix [Proposal] Agent Autonomy Patterns — Undo Stacks & Atomic Operations [1 comments, 2 participants]