By ChipFlow
Map your repo structure to detect naming clashes and doc gaps, track cross-session goals and learnings, build evolving narratives from git history, and auto-generate READMEs—persisting tribal knowledge for fast code exploration.
Show a summary of potential naming clashes detected in the codebase with analysis.
Debug context-tools plugin status
Mark the current goal step as complete and advance to the next
Set the focused step for your current goal
Create a new cross-session goal with guided setup
Admin access level
Server config contains admin-level keywords
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Modifies files
Hook triggers on file write and edit operations
Modifies files
Hook triggers on file write and edit operations
Context Daddy is a sophisticated code understanding plugin for Claude Code that fundamentally changes how AI assistants explore and comprehend large codebases. By combining tree-sitter parsing, intelligent caching, and a custom MCP (Model Context Protocol) server, we're creating a system that can quickly generate semantic maps of entire repositories and provide fast, targeted code retrieval without overwhelming context windows. The project now includes narrative documentation tools that capture the evolving "tribal knowledge" of codebases - the stories, gotchas, and hard-won insights that traditional documentation misses.
Built in tools include:
Understanding code isn't just about parsing syntax. It's about the stories - "here be dragons", "we did X because Y", "this is WTF but it works". That knowledge lives in people's heads and gets lost.
context daddy captures both: fast code exploration AND the narrative that makes codebases actually understandable.
# Install
claude plugin marketplace add chipflow/context-daddy
claude plugin install context-daddy
# Verify MCP tools work
claude mcp list # Should show: repo-map: ✓ Connected
# Generate a narrative for your project
cd /path/to/your-project
/context-daddy:story
Or load directly without installing:
claude --plugin-dir /path/to/context-daddy
search_symbols("*Handler") → Find all handler classes
get_symbol_content("AuthService") → Full source with docstrings
get_file_symbols("src/api.py") → Everything in a file
list_files("*.py") → Find files by pattern
Pre-built SQLite index with FTS5. Claude explores your codebase without drowning in context.
Not changelogs. Stories:
/context-daddy:story # Bootstrap from git history
/context-daddy:refresh # Revise after sessions
Written in "we" voice. Opinionated. Updated after context compaction.
Track multi-session objectives that persist across sessions and projects:
/context-daddy:goal-new → Guided goal creation with plan steps
/context-daddy:goal-done → Complete current step, advance to next
/context-daddy:goal-focus → Set which step you're working on
/context-daddy:goal → List, switch, or archive goals
Goals have human-readable slugs and step IDs. The active goal and focused step appear automatically in every session's context.
Hard-won insights that persist:
.claude/learnings.md - Project-specific~/.claude/learnings.md - Global| Command | Purpose |
|---|---|
/context-daddy:story | Bootstrap narrative from git |
/context-daddy:refresh | Update narrative after a session |
/context-daddy:readme | Generate README from narrative |
/context-daddy:map | Regenerate repo map |
/context-daddy:scan | Regenerate project manifest |
/context-daddy:status | Indexing status |
/context-daddy:learn | Manage learnings |
/context-daddy:goal-new | Create a new goal |
/context-daddy:goal | Manage goals |
/context-daddy:goal-done | Complete current step |
/context-daddy:goal-focus | Set focused step |
/context-daddy:help | MCP tools guide |
Three components:
Multiprocess design: Indexing runs in isolated subprocesses (4GB memory, 20 min CPU limit, watchdog). MCP server stays responsive.
Hooks: SessionStart loads context, Stop hook guides reorientation after compaction.
npx claudepluginhub chipflow/context-daddy --plugin context-daddyMake your AI agent code with your project's architecture, rules, and decisions.
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.
Comprehensive C4 architecture documentation workflow with bottom-up code analysis, component synthesis, container mapping, and context diagram generation
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Complete AI coding workflow system. Self-correcting memory + persistent FTS5-indexed research wikis + auto-research loop + multi-LLM council on a single SQLite store. 33 skills, 8 agents, 22 commands, 37 hook scripts across 24 events. Cross-agent via SkillKit.
Create comprehensive documentation for code, APIs, and projects.