From learning-agents
Dispatches subcommands for LearningAgents: create scaffolded agents from templates, run learning cycles on pending session transcripts, report issues from agent sessions.
How this skill is triggered — by the user, by Claude, or both
Slash command
/learning-agents:learning-agentsThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Manage auto-improving AI sub-agents that learn from their mistakes across sessions.
Manage auto-improving AI sub-agents that learn from their mistakes across sessions.
$ARGUMENTS is the text after /learning-agents (e.g., for /learning-agents create foo, $ARGUMENTS is create foo).
!ls -1 .deepwork/learning-agents/ 2>/dev/null || echo "(none)"
Before routing, check if .claude/session_log_folder_info.md exists. If it does not exist, run Skill learning-agents:setup first, then continue with routing below.
Only perform this check once per session — after the setup skill completes (or if the file already exists), proceed directly to routing for all subsequent invocations.
Split $ARGUMENTS on the first whitespace. The first token is the sub-command (case-insensitive); the remainder is passed to the sub-skill. Accept both underscores and dashes in sub-command names (e.g., report_issue and report-issue are equivalent).
create <name> [template-path]Create a new LearningAgent scaffold. If a template path is provided, the new agent is seeded with the template agent's knowledge files as a starting point.
Invoke: Skill learning-agents:create-agent <name> [template-path]
Example: $ARGUMENTS = "create rails-activejob" → Skill learning-agents:create-agent rails-activejob
Example: $ARGUMENTS = "create new-agent .deepwork/learning-agents/existing-agent" → Skill learning-agents:create-agent new-agent .deepwork/learning-agents/existing-agent
learnRun the learning cycle on all pending session transcripts. Any arguments after learn are ignored.
Invoke: Skill learning-agents:learn
report_issue <agentId> <details>Report an issue with a LearningAgent from the current session.
Invoke: Skill learning-agents:report-issue <session_log_folder> <details>
To construct the session log folder path: search .deepwork/tmp/agent_sessions/ for a subdirectory whose name contains the provided agentId. The path structure is .deepwork/tmp/agent_sessions/<session_id>/<agentId>/. If no match is found, inform the user. If multiple matches exist, use the most recently modified one.
Example: $ARGUMENTS = "report_issue abc123 Used wrong retry strategy" → find folder matching abc123 under .deepwork/tmp/agent_sessions/, then Skill learning-agents:report-issue .deepwork/tmp/agent_sessions/sess-xyz/abc123/ Used wrong retry strategy
Display available sub-commands:
LearningAgents - Auto-improving AI sub-agents
Available commands:
/learning-agents create <name> [template-path] Create a new LearningAgent
/learning-agents learn Run learning cycle on pending sessions
/learning-agents report_issue <agentId> <details> Report an issue with an agent
Examples:
/learning-agents create rails-activejob
/learning-agents create new-agent .deepwork/learning-agents/existing-agent
/learning-agents learn
/learning-agents report_issue abc123 "Used wrong retry strategy for background jobs"
$ARGUMENTS doesn't match any known sub-command, show the help text abovenpx claudepluginhub unsupervisedcom/deepwork --plugin learning-agentsScaffolds LearningAgent directories with core-knowledge.md and Claude Code agent files. Runs bash script, handles templates, and guides interactive domain configuration. Invoke with /create-agent <name> [template].
Use when an agent's performance is uneven and you want systematic improvement. Runs diagnose -> challenge-gen -> challenge-run -> update learnings in a loop. Works with or without a team. Keywords: active-learn, training, adversarial, improve, agent, loop, capability, tuning, solo.
Enables AI agents to learn from experience across sessions by separating journaled memory from policy changes. Includes structured templates for error pattern recognition and success pattern collection.