Cline context engineering playbook: Focus Chain and key tools

Overview

Cline outlines a practical approach to “context engineering,” describing how its system assembles instructions, tools, environment details, file previews, and interaction history at each turn, then manages that state as tasks evolve. The post emphasizes that larger context windows are useful, but the orchestration layer—how relevant tokens are curated, summarized, and passed forward—has greater impact. The stated goal is to keep only what matters in view.

The guidance is positioned as optional: Cline is described as working without manual tuning (assuming a quality coding model), but the playbook documents how to apply specific controls when tasks grow complex or long-running.

Defaults Cline recommends leaving on

Focus Chain

The post recommends leaving Focus Chain enabled. It is on by default in v3.25. At task start, Cline generates a todo list and periodically reinjects it into context so the thread does not drift. The reminder interval is configurable; the default is every six messages. The list functions as a living scope; editing the markdown (adding or reordering steps) causes Cline to adapt. Documentation and background:

• Focus Chain docs: https://docs.cline.bot/features/focus-chain?ref=cline.ghost.io
• v3.25 release note: https://cline.bot/blog/cline-v3-25?ref=cline.ghost.io
• Related essay: https://cline.bot/blog/focus-attention-isnt-enough?ref=cline.ghost.io

Auto Compact

Auto Compact is described as always on. As the context window fills, Cline creates a comprehensive summary, replaces the accumulated history with that summary, and continues without losing decisions, code changes, or state. When Focus Chain is active, its todo list persists through summarization. Documentation:

• Automatic Context Summarization: https://docs.cline.bot/features/auto-compact?ref=cline.ghost.io

Tools to pull on demand

Deep Planning

For substantial features, refactors, or integrations, Deep Planning (/deep-planning) conducts a silent investigation of the codebase, asks targeted questions, and writes an implementation_plan.md. Cline then opens a fresh task that references this plan so implementation starts with distilled context. The post suggests using it when more than a couple back-and-forths are expected to clarify scope, to avoid polluting the execution window with exploration.

• Docs: https://docs.cline.bot/features/slash-commands/deep-planning?ref=cline.ghost.io

Editing Messages and Checkpoints

When a request needs rewriting rather than incremental correction, the guidance is to edit the earlier message that set the task off course, then select either Restore Chat (keep workspace state) or Restore All (rewind files and chat). This resets the conversation and workspace to a clean trajectory.

• Docs: https://docs.cline.bot/features/editing-messages?ref=cline.ghost.io
• Deep dive: https://cline.bot/blog/how-i-learned-to-stop-course-correcting-and-start-using-message-checkpoints?ref=cline.ghost.io

Smol (/smol or /compact)

Smol compresses the conversation in place and continues within the same task, useful during deep debugging or exploratory spikes where flow should not be interrupted. It is the same action as Auto Compact but triggered manually.

• Docs: https://docs.cline.bot/features/slash-commands/smol?ref=cline.ghost.io

New Task (/newtask)

New Task packages only the essentials—plan, decisions, relevant files, and next steps—into a fresh task. The post frames this as a clean slate for implementation after research, or a crisp handoff between collaborators.

• Docs: https://docs.cline.bot/features/slash-commands/new-task?ref=cline.ghost.io
• Background: https://cline.bot/blog/unlocking-persistent-memory-how-clines-new_task-tool-eliminates-context-window-limitations?ref=cline.ghost.io

Memory Bank and .clinerules

The post recommends Memory Bank and .clinerules as a baseline on non-trivial projects. Memory Bank stores durable knowledge—product intent, system patterns, tech context, active context, and progress—as Markdown in the repository. .clinerules are version-controlled instructions that Cline reads and, on request, can edit to align its behavior with team preferences. This approach retains institutional knowledge across sessions and teammates without bloated prompts.

• Memory Bank docs: https://docs.cline.bot/prompting/cline-memory-bank?ref=cline.ghost.io
• Reference rule: https://github.com/cline/prompts/blob/main/.clinerules/memory-bank.md?ref=cline.ghost.io
• Background on .clinerules: https://cline.bot/blog/clinerules-version-controlled-shareable-and-ai-editable-instructions?ref=cline.ghost.io

Rationale

The post argues that model performance degrades as conversations lengthen and instructions are scattered across many turns. Tool outputs, detours, and mid-stream clarifications can bury the signal. Rather than “send everything,” the recommendation is to deliberately curate, compress, and reset:

• Focus Chain keeps tasks anchored.
• Auto Compact preserves decisions and state while discarding noise.
• /smol and /newtask provide precise control over freeing space.
• Deep Planning front-loads clean context for implementation.

For details on token limits and cost dynamics, Cline links to: https://cline.bot/blog/clines-context-window-explained-maximize-performance-minimize-cost?ref=cline.ghost.io

Applying the playbook

• Feature development: Begin with Deep Planning to produce implementation_plan.md, then execute from a fresh task with Focus Chain as a working checklist. Allow Auto Compact to handle rollover. At transitions or when exploration dominates history, start a New Task to carry only essentials. If requirements were missed and divergence occurs, edit the problematic message, Restore All, and regenerate from the corrected prompt.

• Bug investigation: Proceed normally. If logs and detours inflate the thread, use Smol to condense in place. After identifying the root cause, create a New Task with a short summary of cause, files, and fix steps. Keep Focus Chain on, write tests, and close the loop.

• Multi-day or multi-person work: Keep the Memory Bank current, especially activeContext.md and progress.md. At a stopping point, run New Task to create a clean, scoped follow-up. The next collaborator starts by having Cline read .clinerules and the Memory Bank, then opens the new task with a fresh window and the Focus Chain plan preloaded.

Practical guardrails and defaults

• Focus on high-value tokens: requirements, decisions, exact file paths, function signatures, next steps.
• Prefer reset over piecemeal correction when a thread goes off course; edit the divergent message and restore.
• Use large windows as buffer, not as a crutch; Auto Compact exists for rollover.
• Treat .clinerules as code: version, share, and allow Cline to refine them.
• Defaults the post endorses: keep Focus Chain on (enabled by default in v3.25; default reminder every six messages), use Deep Planning beyond trivial changes, use Smol mid-flow and New Task for handoffs or preserved history, and maintain a light but current Memory Bank.

Resources

• Docs index: https://docs.cline.bot/?ref=cline.ghost.io
• Community: Reddit https://www.reddit.com/r/cline/?ref=cline.ghost.io and Discord https://discord.gg/cline?ref=cline.ghost.io

TL;DR

• Cline’s guidance centers on curating, compressing, and resetting context rather than sending everything.
• Keep Focus Chain on; it anchors tasks and is configurable (default: six-message cadence).
• Auto Compact summarizes when the window fills; Smol triggers that compression manually.
• Use Deep Planning to create implementation_plan.md and start implementation from a clean task.
• New Task carries forward only essentials for a fresh execution window or handoff.
• Maintain Memory Bank and .clinerules to preserve durable knowledge across sessions and teammates.