agent-management

Audit worker agent prompts, playbooks, memories, and logs to fix structural behavioral failures.

Updated Feb 16, 2026
One-click install
npx skills add https://github.com/dzackgarza/lattice_interface --skill agent-management-dzackgarza
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: agent-management
Source: https://github.com/dzackgarza/lattice_interface/tree/main/.skills/agent-management
Command: npx skills add https://github.com/dzackgarza/lattice_interface --skill agent-management-dzackgarza

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Agent behavior auditing and structural debugging to diagnose why autonomous agents fail, produce trivial work, or do not complete tasks.

Core Features & Use Cases

  • Behavioral auditing: identify closure mechanisms, memory poisoning, and premature completion in worker agents.
  • Structural fixes: patch prompts, playbooks, and memories to align agent effort with actual file-state verification.
  • Operational guidance: monitor ntfy notifications, agent_runner logs, and git history to improve reliability across tasks.

Quick Start

Run the agent-management workflow on a failing run to locate root causes, verify findings against transcripts, and apply structural prompt/playbook fixes.

Frequently Asked Questions about agent-management

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I debug autonomous agent behavior and diagnose why tasks fail or produce trivial work?

Prevent autonomous agents from shirking by cross-referencing ntfy notifications, agent_runner logs, and git history to detect premature completion or closure mechanisms. Apply structural fixes across all runs by patching prompts and playbooks, ensuring changes are grounded in transcript evidence to close gaps and prevent future shirking.

Why does my worker agent produce trivial work or fail to complete tasks?

Worker agents produce trivial work or fail tasks due to structural causes like memory poisoning, premature completion, or closure mechanisms. Identify these behavioral failures by auditing prompts, playbooks, memories, and logs to fix the underlying structural issues rather than treating symptoms.

How do I audit agent logs and transcripts to fix structural prompt issues?

Audit agent logs and transcripts by running a workflow on a failing run to locate root causes, verifying findings against transcript evidence, and applying structural prompt or playbook fixes. Cross-reference ntfy notifications, agent_runner logs, and git history to ensure fixes are grounded in evidence and rolled back if they reintroduce failures.

Do I need git history and ntfy notifications to audit agent behavior effectively?

Git history and ntfy notifications are essential for effective agent behavior auditing, as they allow you to monitor operational reliability, cross-reference agent_runner logs, and verify that structural prompt fixes are grounded in transcript evidence and rolled back if failures reappear.

What is the best way to patch agent playbooks and memories without reintroducing previous failures?

The best way to patch agent playbooks and memories is to ground all changes in transcript evidence and research, apply fixes across all runs, and roll back immediately if the patched prompts or playbooks reintroduce previous behavioral failures or closure mechanisms.