$ loading_
Give AI agents a persistent task tree for planning, tracking, and results.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Conductor" yet — see the docs or source repo.
Use Conductor to create a hierarchical task tree for “refactoring the payment module,” split into requirements review, API design, coding, testing, and release. Record status, suggested owner, risks, and final results for each subtask.
A structured task tree with phases, subtask statuses, risk notes, and recorded results for ongoing execution.
Manage a “competitive AI assistant research” project with Conductor: create nodes for information gathering, feature comparison, pricing analysis, user review synthesis, and conclusion summary, then keep adding findings, failed attempts, and next steps under each node.
A continuously updated research task tree that clearly preserves process notes, failure reasons, and interim conclusions.
Use Conductor to build a task tree for a multi-step agent workflow including web search, data extraction, summary generation, and report output. Record errors and retry strategies on failure, and monitor overall progress through the web UI.
A task tree with execution progress, failure-handling logs, and archived results, supporting human monitoring and intervention.
Monitor Codex sessions, summarize status, and manage tmux-based automated continuation.
Expose a CognOS agent system as a JSON graph for full inspection.
Run verified, retryable text extraction, redaction, and normalization workflows safely.
Design, evaluate, refine, and package AI skills with an architecture-first workflow.
Combine structured reasoning and execution so agents can think, act, and trace decisions.
Guide agents through structured workflows with flexible step execution and tool calls.