7 Sacred Tips to Best Use Claude Code

2026-02-26

Key Takeaways

Configure a CLAUDE.md file with project conventions, build commands, and style guidelines to give Claude persistent context every session
Plan before you code — use Plan Mode (Shift+Tab) to generate detailed implementation strategies before writing a single line
Manage context aggressively — clear conversations between tasks, use handoff documents, and keep CLAUDE.md under 500 lines
Automate repetitive steps with custom hooks, slash commands, and skills to eliminate manual approval loops and format checks
Break complex problems into smaller tasks and use subagents for parallel, isolated work that doesn’t consume your main context window
Write tests and verify outputs using TDD workflows, Playwright MCP, and self-checking prompts to catch errors before they ship
Use Git and GitHub CLI integration to automate commits, PR creation, code reviews, and CI failure investigation

Claude Code logo.

Claude Code is a terminal-first AI coding assistant built by Anthropic that goes far beyond autocomplete. It reads your files, runs shell commands, interacts with Git, refactors entire modules, and executes multi-step tasks from plain English prompts. The difference between frustration and productivity with this tool comes down to how you configure it — developers who adopt structured workflows report measurably fewer iterations and faster results.

These seven tips distill advice from Anthropic’s own documentation, power users who have logged thousands of sessions, and community-tested workflows. Each tip targets a specific lever that improves Claude Code’s output quality, reduces wasted tokens, and lets you delegate more work with confidence.

Tip 1: Build a Strong CLAUDE.md Foundation

The single most impactful thing you can do is create and maintain a CLAUDE.md file. This markdown file loads automatically at the start of every Claude Code session, acting as persistent project memory. Without it, Claude starts each conversation blind — scanning your codebase to figure out build commands, linting rules, and architectural patterns from scratch.

A well-structured CLAUDE.md should include your common bash commands (npm run test, npm run build), code style rules (“Use ES modules, not CommonJS”), key architectural decisions (“State management uses Zustand, see src/stores”), and testing conventions. Steve Sewell, founder of Builder.io, noted that after adopting Claude Code full-time, one of the first things he had Claude do was generate a CLAUDE.md file with project-specific commands and conventions.

Keep the file under 500 lines. If your documentation grows beyond that, move reference material into skills — these are separate markdown files Claude loads only when needed. CLAUDE.md files support hierarchy too: a global file at ~/.claude/CLAUDE.md applies everywhere, while project-level files in ./CLAUDE.md and even subdirectory files add specificity. Claude prioritizes the most nested, most specific file when instructions overlap.

How to start: Don’t write a CLAUDE.md on day one. Begin with nothing. When you catch yourself repeating the same instruction (“always use Prettier,” “run type-check after edits”), add that line. Let the file grow organically from real friction points. Periodically review it — outdated instructions create noise that degrades performance.

Tip 2: Plan Before You Code

Jumping straight into implementation is the fastest way to burn tokens and get poor results. Power users across multiple community guides agree on this: planning before coding is non-negotiable for anything beyond trivial edits.

Claude Code offers a dedicated Plan Mode, accessible by pressing Shift+Tab or typing /plan. In this mode, Claude enters a read-only phase. It analyzes your codebase, gathers context, and produces a detailed implementation strategy — without writing any code. This mirrors how a senior engineer operates: understand the problem, map out the approach, then execute.

The workflow has four steps. First, ask Claude to create a plan. You can use phrases like “think hard about this” to give it more computational budget. Second, explicitly tell it not to write code yet. Third, review the plan, challenge its assumptions, and refine until you’re satisfied. Fourth, give the green light to implement.

When the plan is ready, Claude offers options including clearing context and starting fresh with only the plan loaded. The fresh instance sees a clean context — no accumulated noise from the exploration phase — and focuses purely on execution.

For complex features spanning multiple files, this approach catches architectural mistakes before they cascade. One practitioner reported that planning reduces bugs by over 30% and cuts down the back-and-forth that burns through your 200,000-token context window.

Tip 3: Manage Context Like a Scarce Resource

Claude Code’s context window is 200,000 tokens for Opus 4.5. That sounds like a lot until you realize the system prompt and tool definitions consume roughly 19,000 tokens (about 10%) before you type your first message. Add CLAUDE.md, MCP server definitions, and conversation history, and your usable space shrinks fast.

Context degradation is the primary failure mode in Claude Code. As conversations grow longer, performance drops. Claude starts losing track of earlier instructions, skills may not trigger correctly, and response quality declines.

The fix is aggressive context hygiene. Use /clear every time you start a new topic. Don’t let old conversation history sit around consuming tokens and forcing compaction. When switching tasks, start a fresh session.

For longer workflows that span multiple sessions, create handoff documents instead of relying on automatic compaction. Before ending a session, ask Claude to write a HANDOFF.md that summarizes the current state: what’s been done, what worked, what didn’t, and the next steps. Then start a fresh conversation and point the new instance at that file. The new agent gets a clean context with all the relevant information and none of the noise.

Context Management Strategy	When to Use	Token Cost
`/clear`	Between unrelated tasks	Resets to zero
Handoff documents (HANDOFF.md)	Multi-session projects	One file load per session
Skills (on-demand loading)	Reference material, workflows	Only loads when invoked
Subagents (isolated context)	Parallel research, large file analysis	Zero on main session
Disable auto-compact + manual control	Power users wanting full control	Depends on timing

One advanced technique from the community: use the half-clone approach. When a conversation gets too long, keep only the later half and start fresh. This preserves recent work while dropping the early exploration that’s no longer relevant.

Tip 4: Automate Repetitive Steps with Hooks and Slash Commands

Every time Claude asks “Can I edit this file?” or “Can I run lint?” — and you already know the answer is yes — you’re losing momentum. Hooks and custom slash commands eliminate these interruptions by automating predictable actions.

Hooks are shell commands that execute at specific points in Claude Code’s lifecycle. You can trigger them before a tool runs (PreToolUse), after it completes (PostToolUse), when Claude sends a notification, or when it finishes responding (Stop). A common setup runs Prettier on every file edit and type-checks TypeScript files after modifications:

{
  "hooks": [
    {
      "matcher": "Edit|Write",
      "hooks": [
        {
          "type": "command",
          "command": "prettier --write \"$CLAUDE_FILE_PATHS\""
        }
      ]
    }
  ]
}

This goes in .claude/settings.json in your project directory. The matcher field supports exact strings or regex patterns. Hooks run outside the AI loop entirely — no tokens consumed, no LLM decisions involved. They’re deterministic scripts that fire on events.

Custom slash commands are even simpler. Create a .claude/commands folder, add a markdown file named after your command, and write instructions in natural language. A /test command might say: “Create comprehensive tests for: $ARGUMENTS. Use Jest and React Testing Library. Mock Firebase dependencies. Include edge cases.” Then typing /test MyButton runs exactly that workflow.

You can also use the interactive /hooks menu inside Claude Code to configure hooks through a guided interface instead of editing JSON directly. The combination of hooks for automated quality checks and slash commands for on-demand workflows eliminates the most common sources of friction in daily use.

Tip 5: Break Down Complex Tasks and Use Subagents

When Claude Code can’t solve a problem in one shot, the issue is almost always scope — the task is too large or too ambiguous. The fix is the same principle that makes good software engineers effective: decompose the problem.

Instead of asking Claude to build an entire feature at once (going from A straight to B), break it into sequential sub-problems: A → A1 → A2 → A3 → B. One developer building a voice transcription system split it into discrete stages — first an executable that downloads a model, then one that records audio, then one that transcribes pre-recorded audio — and combined them only after each piece worked independently.

For tasks that benefit from parallel work or require reading many files, subagents are the right tool. A subagent runs in its own isolated context window, completely separate from your main conversation. It might scan dozens of files or run extensive searches, but your main session receives only a summary. This keeps your primary context clean.

Feature	Best For	Context Impact
Breaking tasks manually	Sequential problem solving	Uses main context
Subagents (foreground)	Isolated research, file analysis	Zero on main session
Subagents (background, Ctrl+B)	Long-running tasks you want to continue past	Zero on main session
Agent teams	Parallel independent sessions with shared tasks	Each agent has own context

You can customize subagents by specifying which model to use (Opus for complex work, Sonnet or Haiku for simpler tasks), whether they run in the foreground or background, and which skills to preload. Press Ctrl+B during a long-running command to move it to the background, freeing you to continue other work.

Skills and subagents combine naturally. A /review skill can spawn separate security, performance, and style-checking subagents that work in parallel and report back independently. Each subagent loads only the skills it needs, keeping overhead minimal.

Tip 6: Write Tests and Verify Outputs Systematically

AI makes mistakes. Treating Claude Code’s output as correct by default is how bugs slip into production. The developers getting the best results build verification into every workflow.

Test-Driven Development (TDD) works exceptionally well with Claude Code. Write tests first, confirm they fail, commit them, then ask Claude to write code that makes them pass. This gives Claude a concrete target and you a reliable way to verify the implementation. Review the tests yourself to ensure they actually check meaningful behavior — not just returning true.

For autonomous tasks like git bisect (finding which commit broke something), Claude needs a way to test each commit programmatically. The pattern uses tmux: start a session, send commands to it, capture the output, and verify the result. Claude can then loop through commits automatically, testing each one until it finds the failure.

Beyond code tests, develop a habit of asking Claude to verify its own work. One effective prompt: “Double check everything — every single claim in what you produced — and at the end make a table of what you were able to verify.” Self-checking doesn’t guarantee accuracy, but it catches a surprising number of errors, especially in research or analysis tasks.

For visual verification, Playwright MCP is the strongest option for browser automation. It focuses on the accessibility tree (structured element data) rather than screenshots, making it more reliable for most tasks. Claude’s native browser integration (/chrome) works better when you need to interact with logged-in browser sessions or click elements by visual coordinates. Use Playwright by default and Chrome integration only when specifically needed.

Visual Git clients like GitHub Desktop provide another verification layer. Have Claude create draft PRs so you can review all changes in a familiar interface before anything goes live.

Tip 7: Leverage Git and GitHub CLI Integration

Claude Code’s integration with Git and the GitHub CLI (gh) turns it into an effective DevOps partner that handles the operational work most developers find tedious.

For daily Git operations, let Claude handle commits (so you never write commit messages manually), branching, pulling, and creating draft PRs. Draft PRs are particularly useful — Claude handles the PR creation process with low risk, and you review everything before marking it ready. The GitHub CLI is powerful enough to run arbitrary GraphQL queries, pull PR edit histories, and manage issues programmatically.

For automated code review, the /install-github-app slash command sets up Claude to automatically review your pull requests on GitHub. Out of the box, the reviews are verbose — Claude comments on every minor detail. Customize the review prompt in claude-code-review.yml to focus on what matters:

direct_prompt: |
  Please review this pull request and look for bugs and security issues. Only report on bugs and potential vulnerabilities you find. Be concise.

This narrows Claude’s focus to actual logic errors and security issues — the things human reviewers typically miss while they nitpick variable names.

For CI failure investigation, Claude Code excels at the work nobody wants to do: wading through GitHub Actions logs to find root causes. Point Claude at a failed CI run and ask it to dig into the issue. If the initial answer is surface-level, push deeper — ask whether a particular commit, PR, or flaky test caused the failure. Claude can navigate logs, identify breaking commits, and even create draft PRs with fixes.

You can also disable the default co-authored-by attribution Claude adds to commits and PRs by setting both values to empty strings in ~/.claude/settings.json:

{
  "attribution": {
    "commit": "",
    "pr": ""
  }
}

The combination of automated commits, intelligent PR reviews, and CI debugging turns Claude Code from a coding assistant into a full development workflow partner. As one power user put it: the tool handles the tasks you find boring or too tedious, freeing you to focus on the decisions that actually require human judgment.

Final Word

Claude Code rewards the developers who treat it as a configurable system rather than a magic box. The seven practices covered here — building a strong CLAUDE.md, planning before coding, managing context aggressively, automating with hooks and slash commands, decomposing problems with subagents, verifying outputs through tests, and leveraging Git integration — form a layered workflow where each piece reinforces the others.

None of these tips require advanced technical knowledge. A well-maintained CLAUDE.md takes minutes to set up. Plan Mode is a single keyboard shortcut. Hooks are a few lines of JSON. The gains compound over time: less repetition, fewer wasted tokens, cleaner code, and more tasks you can confidently delegate while you focus on architecture and decision-making.

The developers seeing the strongest results share one habit — they invest time in their own workflow. They notice when they repeat an instruction for the third time and add it to CLAUDE.md. They spot a recurring approval prompt and write a hook. They hit a context limit and build a handoff process. Each small improvement stacks, and within weeks the tool operates at a level that feels qualitatively different from where they started.

Start with Tip 1. Add the rest as friction appears. The best configuration for Claude Code is the one that solves the problems you actually encounter, not a theoretical ideal copied from someone else’s setup.

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Sources: Claude Code, ykdojo on GitHub, Builder.io

Written by Alius Noreika