VS Code AI agents can work against a Kanban task when the board is connected through the AgentKanban extension. You create a card with @kanban /new <title>, select it with @kanban /task <task name>, and run the documented plan, todo, and implement loop. The selected card is written into a managed section of AGENTS.md and local Markdown files, while MCP configuration lets supported agents read or update board data.
The important limitation is prioritization: the documented workflow is user-directed, not an autonomous ranking system. You choose the active task, arrange work on the board, and decide which agent session to run. VS Code’s native Plan agent can then investigate the selected work, produce a reviewable implementation plan, and wait for your approval before changes begin.
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What the Kanban–agent connection actually does
AgentKanban is a VS Code extension that links a workspace to a Kanban board. It treats the selected board card as working context for an AI coding session rather than as a separate list that the model merely reads once.
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When you select a board and task, the extension immediately updates a managed section of AGENTS.md and local board documents. Those files give the coding agent a durable description of the task, its current state, and related notes. Opening a new chat or agent session therefore does not require you to paste the entire card again.
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Several channels can carry task information
The workflow can use the managed AGENTS.md section, .agentkanban/MEMORY.md, and .agentkanban/TECHNICAL.md. The extension also writes MCP configuration so supported agents can read and update the board through tools. Optional capture can copy prompts and agent responses back to the task, but capture is opt-in and starts only after you enable it.
These channels have different jobs. AGENTS.md is the selected-task handoff an agent sees in the workspace. The Markdown files hold longer-lived memory and technical notes. MCP provides an active tool connection to the board. Turn capture records conversation context when you explicitly choose that behavior.
What you need before creating a task
- VS Code with the AgentKanban extension installed.
- A workspace opened in VS Code and connected to a Kanban board through the extension.
- An agent harness supported by the extension, such as GitHub Copilot or Claude Code.
- Permission to edit the repository and, if you use MCP updates, permission for the configured agent tools to change board data.
- A decision about whether prompts and responses should be captured. Capture is optional; it is not silently enabled by selecting a task.
Extension labels and agent-window behavior can change as VS Code and the extension evolve. If a command is not recognized, check that the extension is enabled in the current workspace and that the agent session is running in the workspace containing the generated files.
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Create a Kanban task from VS Code
The documented creation command is available from an agent chat:
@kanban /new <title>Replace <title> with a concise outcome, such as Handle expired session tokens. The title should describe the result rather than a vague activity; this is what you will later use to select the card and distinguish it from other work.
- Open the repository workspace in VS Code.
- Start the supported agent chat.
- Send
@kanban /new <title>. - Confirm that the new card appears on the connected board and that the workspace context has been updated.
Creation is separate from implementation. The command creates the task; it does not by itself authorize code changes or decide how the task should be broken down.
Select the card that an agent should work on
Before asking an agent to plan or edit code, bind the session to one card:
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/taskcommand with the card’s task name. - Verify that the selected task is reflected in the managed
AGENTS.mdsection and the local board documents. - Only then ask the agent to inspect the repository or begin the task workflow.
Selection matters because the extension uses the active task to refresh context and to associate subsequent updates. If you switch cards, the managed context changes immediately; an agent that continues working without noticing the switch may be operating on the wrong objective.
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Run the documented plan–todo–implement loop
AgentKanban describes a Markdown-based workflow inside VS Code. Treat each phase as a distinct checkpoint rather than sending one oversized instruction.
1. Plan the work
After selecting the task, ask the agent to plan. In this phase, the agent examines the project and turns the card into an implementation approach. A useful plan identifies the files or subsystems likely to change, dependencies, tests, and decisions that still need your input.
Read the plan before implementation. If the agent misunderstood the card, correct the task context now instead of allowing an incorrect plan to become code. The board remains the durable task record; the plan explains how the repository can satisfy it.
2. Record the todo work
Use todo to turn the plan into actionable items. Keep items small enough to verify independently, for example: add a regression test, update the token-validation service, then document the configuration change.
A todo list is useful for steering an active session. You can reorder or clarify items on the board and in the task context before implementation. Do not treat the list as an automatic priority score; its order reflects your decisions.
3. Implement deliberately
When the plan and todo list are acceptable, instruct the agent to implement. In agent mode, Copilot determines which files to change, can propose terminal commands, and iterates to remediate issues until the requested task is complete. It can also accept follow-up prompts while it works, so you can narrow scope, correct a mistaken assumption, or change which todo item should be handled next.
Review the proposed edits, command output, and tests as they appear. “Implement” is an execution instruction, not a substitute for code review or Git review.
Update a task while an agent is working
There is no single update path. Choose the channel that matches the information you are changing.
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Update the managed task context
Changing the selected card or its board state causes the extension to refresh the managed section of AGENTS.md and the local board documents. This is the simplest way to make a changed objective visible to the next prompt or session. After a substantial board edit, ask the agent to reread the current task before it continues.
Keep durable memory and technical notes
Use .agentkanban/MEMORY.md for decisions and facts that should survive a session boundary. Use .agentkanban/TECHNICAL.md for implementation details, constraints, or system notes that future work needs. Keeping these files focused prevents a later agent from confusing temporary chat discussion with an enduring project decision.
Use MCP for board-side changes
The extension writes MCP configuration so supported agents can access board operations directly. When the agent has the required MCP connection and permissions, it can read task data and perform supported updates from the session. Confirm the resulting board state rather than assuming a tool call succeeded, especially after changing workspaces or agent configurations.
Capture turns only when you want an audit trail
Optional capture can send prompts and agent responses back to the task. Enable it intentionally when a conversation record is useful for handoff or review. Because capture is opt-in, a task will not contain previous chat turns unless you enabled that feature and allowed the session to record them.
Refresh after context drift
If the agent starts discussing an old card, stale requirements, or a previous branch, re-inject the current task:
@kanban /refreshUse /refresh after switching tasks, editing the board outside the current chat, or reopening a session whose context is incomplete. It restores the selected task context; it does not undo code changes already made.
How to prioritize tasks
Prioritization in this workflow is explicit and human-directed. The documented behavior does not include an automatic priority score, due-date optimizer, or autonomous card reordering agent.
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Decide which card should be active, then select it with @kanban /task <task name>. Arrange the board according to your team’s policy and choose the next session to run. The extension supplies context for that choice; it does not make the choice for you.
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Use the Agents window to manage competing sessions
VS Code’s Agents window is designed for assigning tasks, managing multiple sessions, following progress, and reviewing results. This makes it useful when several cards are ready: assign a session to the task you have chosen, monitor its progress, and keep other cards queued rather than allowing multiple agents to guess which work matters most.
Change priority during execution with a follow-up
Agent mode accepts follow-up prompts while it works. If a security issue becomes more urgent than a planned refactor, tell the active agent which scope to stop, which todo item to handle, and what must remain untouched. Update the board as the source of the new decision, then use /refresh if the session needs the revised context injected again.
What you should not expect
Nothing in the documented workflow independently ranks cards from repository signals, estimates throughput, optimizes due dates, or reorders the board without your instruction. If your team needs those policies, encode them in board conventions and review them manually before assigning the next agent session.
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Keep context when starting a new agent session
A new session can be reliable when the task context is stored in the workspace rather than only in chat history.
- Select the intended card with
@kanban /task <task name>. - Confirm that the managed
AGENTS.mdsection names the current task. - Read the relevant entries in
.agentkanban/MEMORY.mdand.agentkanban/TECHNICAL.mdbefore asking for new work. - Start the new Copilot or Claude Code session in the same workspace.
- If the agent shows stale or missing information, send
@kanban /refresh. - Ask for a short restatement of the task and constraints before continuing implementation.
Turn capture can provide additional continuity, but it is not a replacement for maintaining the Markdown context. A future agent should be able to understand the objective and technical decisions even when no earlier conversation was captured.
Isolate risky work with a worktree
For a broad change or a task that could destabilize the main checkout, use:
@kanban /worktreeThe extension creates a task branch and a separate working directory, writes task-specific AGENTS.md content, and opens that worktree in VS Code. The agent can then edit and test in isolation while the main workspace remains unchanged.
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When a worktree is appropriate
- The task touches many files or has uncertain scope.
- You need to run an experimental migration or dependency change.
- Several agent sessions must work in parallel without sharing uncommitted files.
- You want a clean review point before merging into the main branch.
What the worktree does not do
It does not replace normal Git review. Inspect the branch, run the project’s tests, and merge it through your usual workflow after the agent finishes. If the task is small and low-risk, a separate worktree may add more coordination overhead than protection.
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AgentKanban versus VS Code’s native Plan agent
These features solve different parts of the process. AgentKanban supplies durable Kanban state and task context; the native Plan agent structures the implementation decision inside VS Code.
| Capability | AgentKanban workflow | VS Code native Plan agent |
|---|---|---|
| Task creation surface | @kanban /new <title> in agent chat creates a board task. |
Starts from an assigned coding request in VS Code; the documented feature is planning rather than creating a Kanban card. |
| Context persistence | Managed AGENTS.md, .agentkanban/MEMORY.md, .agentkanban/TECHNICAL.md, MCP, and optional turn capture. |
Produces a reviewable plan in the VS Code agent workflow; board persistence must come from your Kanban process. |
| Status and priority | You select the active task and manage board order; no automatic ranking is documented. | You assign sessions and choose whether to approve, implement, autopilot, or reject the plan. |
| Tool integration | MCP configuration lets supported agents read and update board data. | Uses VS Code’s agent tooling to research the project and prepare implementation. |
| Isolation | @kanban /worktree creates a task branch and separate working directory. |
Isolation depends on the workspace and Git setup you provide. |
| Approval controls | The plan–todo–implement loop leaves the decision with you before implementation. | Offers Implement Plan, Approve Plan Only, Implement with Autopilot, or Reject actions. |
A practical combination is to select and prioritize the card in Kanban, ask the native Plan agent to investigate and produce a plan, approve or revise that plan, and then let the coding agent implement within the selected workspace or worktree.
End-to-end operating procedure
- Create or identify the card. Use
@kanban /new <title>for new work, or select an existing card. - Choose priority yourself. Put the card in the appropriate board position and decide whether it should run now.
- Bind the session. Send
@kanban /task <task name>and confirm the managed context changed. - Choose the workspace safety level. Stay in the main checkout for contained work; use
@kanban /worktreefor broad or risky changes. - Plan. Ask the agent to inspect the repository and produce a plan with assumptions, files, tests, and unresolved questions.
- Review and create todos. Convert accepted work into ordered, testable items.
- Implement. Give the agent the
implementinstruction and monitor edits, commands, and test output. - Steer when needed. Use follow-up prompts to correct scope or change the next todo item.
- Persist decisions. Put durable conclusions in the task context or the appropriate Markdown file rather than relying on chat memory.
- Refresh after a switch. Send
@kanban /refreshwhenever the session’s context is stale. - Review the result. Check the diff, tests, branch, and board state before merging or moving the card onward.
Troubleshooting common failures
The command is not recognized
Check that AgentKanban is installed and enabled for the current workspace, that the chat is an agent chat rather than an ordinary text conversation, and that the command begins with the exact @kanban prefix. Reopen the workspace if the extension was installed while it was already open.
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Stop the current instruction, select the intended card with @kanban /task <task name>, and run @kanban /refresh. Verify the managed AGENTS.md section before allowing further edits.
Board changes are not appearing in the agent
Confirm that the agent is running in the workspace connected to the board and that the local Markdown files changed after selection. Refresh the context. If you rely on MCP, verify that the extension-generated configuration is available to the current agent harness and that its permissions allow board access.
A new session has no history
Read AGENTS.md, .agentkanban/MEMORY.md, and .agentkanban/TECHNICAL.md. If conversation continuity is required, enable optional turn capture before the work begins; previous turns cannot be reconstructed retroactively when capture was disabled.
The agent changed more than intended
Use the Git diff and test results to identify the scope, then give a follow-up instruction that names the files or behavior to preserve. For future high-risk tasks, use a worktree and require a reviewed plan before implementation.
Quick Recap
Controls for safe team use
- Make one card the explicit active task before each agent session.
- Keep task titles outcome-oriented so
/taskselection is unambiguous. - Store architectural decisions and constraints in the Markdown context files.
- Enable turn capture only when the team is comfortable recording prompts and responses in the task.
- Review MCP permissions and generated configuration when changing agent harnesses or workspaces.
- Use worktrees for changes whose failure would disrupt the main checkout.
- Require human review of plans, diffs, tests, and merges; the workflow does not provide automatic priority judgment or approval.
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