Feature Request: A Structured Workflow for Complex, Long-Running Tasks to Improve Agent Reliability and Focus

Title: Feature Request: A Structured Workflow for Complex, Long-Running Tasks to Improve Agent Reliability and Focus

Labels: feature-request, enhancement, agent-reasoning, agent-reliability

Is your feature request related to a problem? Please describe.

First, I want to express how incredibly powerful Claude Code is. The agentic capabilities, combined with features like the TodoWrite tool, /compact command, and auto-compaction, make it an indispensable part of my daily workflow.

I've been pushing the boundaries of what's possible with Claude Code on increasingly complex, long-running tasks—such as implementing large features from scratch, refactoring core modules across multiple files, or debugging subtle architectural issues. Through these sessions, I've observed a recurring challenge: on tasks that span dozens of conversational turns, the agent can sometimes "lose the thread" of the original, high-level objective.

As a conversation progresses, the context window accumulates not just the essential code, but also a significant amount of "noise":

• The output of numerous Read, Grep, and Glob commands from initial exploration.
• The agent's own exploratory reasoning and intermediate thoughts.
• User corrections, clarifications, and iterative feedback.
• Code diffs from previous, sometimes abandoned, attempts.

This "context pollution" degrades the signal-to-noise ratio within the context window. The original goal gets "lost in the middle," which can lead to the agent drifting from the plan, repeating work, or requiring more frequent manual re-direction to get back on track. While the existing auto-compact feature is excellent for managing context window size, it doesn't fully solve the problem of maintaining a high-signal focus throughout a marathon task.

Describe the solution you'd like

I propose a new, integrated "Complex Task Mode" designed to dramatically improve Claude Code's reliability, focus, and success rate on these ambitious, multi-turn workflows. This would be a structured system composed of three complementary phases that build upon and enhance existing capabilities.

1. A Dedicated "Planning & Scoping" Phase

To prevent the noise from the exploratory phase from affecting the implementation, this phase would separate planning from execution. It could be initiated by a new command, like /plan-task.

How it would work:

1. Autonomous Investigation: Claude Code enters a non-verbose investigation mode. It uses its read-only tools (Read, Grep, Glob, LS) to thoroughly analyze the codebase, understand dependencies, and build a mental model of the task.
2. Targeted Clarification: After its initial investigation, it engages the user with targeted questions to resolve ambiguities.
3. Formal Plan Generation: The agent produces a comprehensive implementation_plan.md file in the project root. This plan would outline the full strategy, files to create/edit, and a step-by-step checklist.
4. Clean Handoff: This is the most critical step. Upon user approval, Claude Code would start a new, clean session or sub-agent task. The initial context for this new session would be minimal and high-signal, containing only the user's original high-level request, the generated @implementation_plan.md, and any key files explicitly @-mentioned in the plan. This ensures the execution phase begins with a perfect, distilled set of instructions.

2. Persistent Goal Reinforcement via an "Active Checklist"

To keep the agent locked on its objective during the long implementation phase, this feature would elevate the existing TodoWrite tool into a persistent "north star."

How it would work:

1. From the implementation_plan.md, a checklist of high-level tasks is automatically generated.
2. This checklist is displayed in the UI and, crucially, is periodically and automatically re-injected into the context window every 5-10 turns.
3. As part of its reasoning loop, the agent would be prompted to review and update this checklist, marking items as complete and re-prioritizing what's next.

This "Focus Anchor" mechanism constantly re-orients the agent towards the primary goal, preventing it from getting sidetracked by the accumulating conversational history.

3. Intelligent, State-Preserving Auto-Compaction

This would enhance the existing auto-compact feature to work seamlessly with the new structured workflow, creating a feeling of near-infinite context.

How it would work:

1. When auto-compact is triggered near the context limit, its summarization logic would be intelligently guided by the active plan.
2. It would be instructed to preserve the full, up-to-date state of the implementation_plan.md and the active checklist, along with key architectural decisions and a summary of successfully implemented code.
3. This high-fidelity summary would then replace the bloated conversation history, allowing the agent to continue exactly where it left off with all critical, high-signal context intact.

Example Workflow

1. User: > /plan-task "Refactor our entire authentication system to use OAuth2"
2. Claude: [Planning...] (Silently explores src/auth, src/services, etc.)
3. Claude: I see you're currently using session cookies. Should I replace this system entirely or maintain it for backward compatibility?
4. User: Replace it entirely.
5. Claude: Understood. I've created implementation_plan.md with the proposed steps. Shall I begin execution?
6. User: Yes.
7. (A new, clean session begins, primed with the plan)
8. Claude: [Checklist updated] Okay, starting implementation. First up: create the OAuth2 provider interface in src/auth/providers/...
9. (Dozens of turns later)
10. Claude: [Context is getting full. Compacting conversation to maintain focus...] (The history is summarized, preserving the plan's state, and work continues seamlessly).

Describe alternatives you've considered

Currently, my workaround is a manual and less effective version of this proposal:

1. Ask Claude to make a plan.
2. Manually copy the plan and relevant file paths.
3. Use /clear to start a fresh session.
4. Carefully craft a new prompt that includes the plan and file contexts.
5. Periodically remind Claude of the high-level goals throughout the task.

This manual process is cumbersome and prone to error. An integrated, automated system would be far more robust and would unlock the ability to delegate significantly larger and more complex engineering challenges to Claude Code.

Thank you for your consideration. I believe a workflow like this would be a game-changer and would solidify Claude Code as the leading tool for serious, professional software development.