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Claude Code Prompts — Independently Authored Prompt Collection

Independently written prompt templates for building AI coding agents, inspired by patterns observed in Claude Code. System prompts, tool prompts, agent prompts, memory management, and multi-agent coordination.

Check out RepoWise

RepoWise

Prompts tell your agent how to behave. RepoWise tells it what the codebase actually does.

Open-source codebase intelligence engine. Auto-generated architecture wikis, dependency graphs, ownership maps, dead code detection, and 9 MCP tools your AI editor can query in real time.

GitHub   |   repowise.dev

Scroll down for Claude Code's prompt patterns. 👇


Claude Code System Prompts

We studied how Claude Code behaves in practice -- how it structures safety rules, routes tools, delegates to subagents, manages memory -- and wrote our own prompt collection from scratch implementing the same patterns.

Every prompt in this repo is independently authored. We observed what patterns make a coding agent reliable and wrote our own versions. From the team behind RepoWise.

Not affiliated with Anthropic. See DISCLAIMER.md.

Note ⭐ Star this repository to stay updated. We analyze each Claude Code release and update the patterns here.

What's Inside

Category Files What You Get
System prompt 1 Agent identity, safety rules, code style, tool routing, output format
Tool prompts 11 Shell, file read/edit/write, grep, glob, web search/fetch, agent launcher, ask user, plan mode
Agent prompts 5 General purpose, code explorer, solution architect, verification specialist, documentation guide
Memory prompts 4 Conversation summarization, session notes, memory extraction, memory consolidation
Coordinator prompt 1 Multi-worker orchestration with synthesis, delegation, and verification workflow
Utility prompts 4 Session titles, tool summaries, away recaps, next-action suggestions
Pattern analyses 9 Commentary on each pattern with reusable templates
Cursor skills 3 Drop-in skills for coding standards, verification, and prompt design

Quick Start

  1. Browse the pattern files to understand how production coding agents structure their prompts.
  2. Copy any complete prompt into your own agent configuration.
  3. Replace {{PLACEHOLDER}} values with your stack, tool names, and risk policy.
  4. For Cursor IDE users, drop skills/ into ~/.cursor/skills-cursor/ for instant integration.
  5. Add codebase context with RepoWise so your agent actually understands the project it's working in.

Prompt Engineering Patterns

Patterns observed in how Claude Code structures its prompts — with analysis and independently written templates.

Claude Code System Prompt

The complete system prompt covering identity, permissions, task execution, code style, safety, tool routing, tone, and output efficiency.

Claude Code Tool Prompts

Prompt templates for each tool a coding agent uses to interact with the filesystem, shell, web, and user.

  • Shell Execution — bash command execution with sandbox, git safety, commit/PR workflows
  • File Read — reading files, images, PDFs, notebooks
  • File Edit — exact string replacement with uniqueness constraints
  • File Write — creating new files with read-first safety
  • Search Grep — ripgrep-powered content search
  • Search Glob — fast file pattern matching
  • Web Search — web search with mandatory source citations
  • Web Fetch — URL fetching with AI-powered extraction
  • Agent Launcher — spawning autonomous subagents
  • Ask User — structured multiple-choice questions
  • Plan Mode — entering planning mode before implementation

Claude Code Agent Prompts

Prompt templates for specialized subagents — each designed for a different task type.

Claude Code Memory Prompts

How to manage context across long sessions — summarization, session notes, and persistent memory.

Claude Code Utility Prompts

Small helper prompts for session management and user experience.

Cursor Skills

Drop-in skills for Cursor IDE that implement these patterns directly.

Methodology

We studied how Claude Code behaves in practice and identified the behavioral rules, safety patterns, tool-routing strategies, and multi-agent coordination approaches that make it effective. We then independently authored every prompt in this repository from scratch, implementing the same patterns in our own words.

All content is original.

Pair With RepoWise for Full-Stack Agent Intelligence

The prompts in this repo handle agent behavior: safety, tool routing, delegation, verification. But behavior without context is like a senior engineer who's never seen the codebase. RepoWise fills that gap.

What you get How it helps your agent
Architecture wiki Agent understands module boundaries before making changes
Dependency graphs Agent traces impact of changes across packages
Ownership tracking Agent knows which team/person owns each module
Dead code detection Agent avoids modifying unused code paths
9 MCP tools Agent queries project knowledge directly from Cursor, Claude Code, or any MCP-compatible editor

Works with any language, any repo size.

GitHub | repowise.dev

Legal

  • DISCLAIMER.md — independent authorship, nominative fair use, non-affiliation, DMCA policy.
  • LICENSE — MIT for all original content.
  • CHANGELOG.md — version history.

"Claude Code" is a trademark of Anthropic, used here under nominative fair use to describe the subject matter. This project is independent and not affiliated with Anthropic.

Contributing

  • All additions must be original writing. No verbatim vendor prompt text.
  • Prefer concise, implementation-ready language over theory.
  • Every new pattern file must include at least one concrete template.
  • Follow section conventions: Approach / Output / Constraints for agents, Include / Format / Constraints for memory, Rules / Format for utilities.

Star History

If this helped you build better AI agents, star the repo so others can find it.


Built by RepoWise — open-source codebase intelligence for AI agents (repowise.dev).

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Independently authored prompt templates for AI coding agents — system prompts, tool prompts, agent delegation, memory management, and multi-agent coordination. Informed by studying Claude Code.

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