Bootstrapped Delegate Agents Drift From Packaged Defaults
A CLI tool that bootstraps agent files only copies them if missing, causing users to run stale local definitions indefinitely after package updates. There is no mechanism to detect or sync newer upstream defaults.
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Similar Problems
surfaced semanticallyAgent Output Lacks Provenance and Resolved Model Info
When debugging multi-agent AI workflows, there is insufficient metadata about which agent definition was used and what model was resolved. This makes it difficult to diagnose issues in delegate and subagent handoff flows.
LLM Agents Lose Goal Coherence in Long-Running Sessions
Developers building multi-step LLM agents report that models drift from their original task framing over extended sessions, abandoning planned workflows or producing outputs that deviate from agreed specifications. The problem is particularly acute with architect-style sub-agents expected to maintain consistent behavior across many turns. No reliable mechanism exists to detect or correct drift without full session restarts.
AI Agent Framework Only Supports Claude Despite Multi-Agent Claims
Project claims agent-agnostic support but hardcodes Claude CLI checks. Two config systems do not communicate. Labels not auto-created.
No Automatic Update Notifications for CLI Agent Tools
Developers using CLI-based AI agent tools have no automatic way to know when newer versions are available during normal use, requiring manual polling and causing silent drift on outdated skill versions.
OAuth Token Management for Sandboxed Coding Agents Is Unsolved
Coding agents running in sandboxed environments cannot safely handle OAuth token refresh without risking credential exfiltration. No standard pattern exists for passing authenticated credentials into sandboxes while preventing agents from leaking refreshed tokens.
Problem descriptions, scores, analysis, and solution blueprints may be updated as new community data becomes available.