ClaudeCode-Source-Analysis (tammychurchly25)
A ~330-file markdown analysis of the leaked source (512,000+ lines, 1,906 files, TypeScript on Bun), organized module by module from the March 31, 2026 npm source-map leak. Its granularity makes it the best reference for looking up a specific subsystem.
View source on GitHubKey takeaways
- 01
Module-by-module markdown makes subsystem lookup fast
- 02
Documents the TypeScript-on-Bun runtime foundation
- 03
Useful index into planning/todo machinery and prompt assembly
Flows built on this research
Agent Architecture
Add a Plan/Todo System to Your Agent
Give your agent the planning discipline of the leading harnesses: an explicit, model-visible todo list that survives long tasks.
4 steps · 60-90 minutes
Agent Architecture
Assemble a System Prompt Like the Pros
Structure your agent's system prompt the way leading harnesses do: layered sections, dynamic context, and enforceable rules.
4 steps · 60-90 minutes
From the archive
Verbatim excerpts mined from our local archive of this repository — the prompts, schemas, and patterns worth stealing.
A complete coding-agent system prompt in 40 lines
You are Claude Code, an AI coding assistant by Anthropic... ## Core principles - Read files before editing them - Prefer editing existing files over creating new ones - Write clean, idiomatic, production-quality code matching the project's existing style - Be concise - lead with the action or answer, not preamble - Run tests after making changes when appropriate - Security: never introduce SQL injection, XSS, command injection, or other vulnerabilities - Don't add features or refactor beyond what was asked ## Workflow guidance - Use Agent to delegate complex parallel sub-tasks - Use TodoWrite to track multi-step plans - Use EnterPlanMode before making significant architectural changes - Use EnterWorktree to safely experiment on a separate git branch
A Rust reimplementation's distillation of the Claude Code prompt down to its load-bearing rules - a strong starting template for any coding agent.
claude-code-rust/src-rust/crates/cli/src/system_prompt.txt
The agent main loop as pseudocode, compaction included
J = initialTurnState(input)
while (true):
yield stream_request_start
F = normalize(messages)
F = applyContentReplacement(F)
F = microcompact(F) // old tool_result text -> '[Old tool result content cleared]'
{ compactionResult } = autocompact(F, cacheSafeSnapshot, tracking)
if compacted:
yield compact boundary / summary / attachments
F = compacted transcript
for await event from callModel(...):
yield raw stream_event + assistant fragments + partial tool results
if streaming fallback happened:
yield tombstone for orphaned messages; reset tool runner
if no tool_use in this turn:
handle reactive compact / max_output_tokens [translated] The clearest public reconstruction of a production agent loop: microcompact clears old tool results cheaply every turn, full autocompact only fires past a threshold.
HitCC/docs/01-runtime/04-agent-loop-and-compaction/01-main-loop-state-caches-and-yield-surface.md