Vibecosystem system-overview

Show how vibecosystem works - agents, skills, hooks, and self-learning pipeline.

install

source · Clone the upstream repo

git clone https://github.com/vibeeval/vibecosystem

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/vibeeval/vibecosystem "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/system-overview" ~/.claude/skills/vibeeval-vibecosystem-system-overview && rm -rf "$T"

manifest: skills/system-overview/SKILL.md

System Overview

Show users how Continuous Claude works - the opinionated setup with hooks, memory, and coordination.

When to Use

User asks "how does this work?"
User asks "what can you remember?"
User asks "what's different about this setup?"
User runs
```
/system_overview
```

Response

CONTINUOUS CLAUDE SYSTEM OVERVIEW
=================================

MEMORY LAYER (PostgreSQL + pgvector)
------------------------------------
- 78,000+ temporal facts from past sessions
- Learnings extracted automatically at session end
- Semantic search with embeddings

RECALL: uv run python opc/scripts/recall_temporal_facts.py --query "your topic"

HOOKS (9 event types registered)
--------------------------------
SessionStart    → Load continuity ledger, rebuild symbol index
UserPromptSubmit → Skill activation check, context injection
PreToolUse      → Smart search routing (Grep → TLDR for code)
PostToolUse     → File claims, compiler feedback
PreCompact      → Save state before context compaction
Stop            → Extract learnings, create handoffs
SubagentStart   → Register spawned agents
SubagentStop    → Coordination, handoff creation
SessionEnd      → Cleanup

CONTINUITY SYSTEM
-----------------
Ledger:   thoughts/ledgers/CONTINUITY_CLAUDE-{session}.md
Handoffs: thoughts/shared/handoffs/{session}/*.yaml

Commands:
  /resume_handoff <path>  - Continue from handoff
  /create_handoff         - Create snapshot for transfer

TLDR CODE INTELLIGENCE
----------------------
5-layer analysis: AST → Call Graph → CFG → DFG → PDG
95% token savings vs reading raw files
Auto-intercepts Grep for .py/.ts/.go/.rs files

Pre-built index: /tmp/claude-symbol-index/symbols.json

SETUP
-----
Run: uv run python opc/scripts/setup/wizard.py

Options:
  [1] SQLite only (simple, offline)
  [2] PostgreSQL + pgvector (semantic search)

Key Files

Component	Location
Hook registration	`.claude/settings.json`
Hook implementations	`.claude/hooks/src/*.ts`
Rules (auto-injected)	`.claude/rules/*.md`
Skills	`.claude/skills/*/SKILL.md`
Setup wizard	`opc/scripts/setup/wizard.py`
Recall script	`opc/scripts/recall_temporal_facts.py`
Store learning	`opc/scripts/core/store_learning.py`
Symbol index builder	`opc/scripts/build_symbol_index.py`

Environment Variables

Variable	Purpose
`CONTINUOUS_CLAUDE_DB_URL`	PostgreSQL connection
`VOYAGE_API_KEY`	Embeddings (optional)
`BRAINTRUST_API_KEY`	Tracing (optional)
`CLAUDE_PROJECT_DIR`	Auto-set by Claude Code