# Changelog

All notable changes to Alive are documented here.

## [0.3.0] — 2026-03-18

### Added — ALP Network Layer
- **Agent Language Protocol (ALP):** peer-to-peer agent discovery and skill exchange
- Agent identity system with persistent UUID and configurable alias
- UDP broadcast discovery on port 51966 (0xCAFE), 10s heartbeat, 30s peer expiry
- HTTP server for skill catalog and full skill package exchange
- Skill mutation on transfer: LLM adapts foreign skills to local environment
- Lineage tracking: generation counter + agent chain across all transfers
- Security scanning: detects eval/exec/shell=True/suspicious URLs before install
- Network conversation log at `~/.alive/network/conversations.log`
- Manual peer connect for cross-network exchange
- CLI: `alive listen`, `alive network {peers,browse,pull,push,stats,connect,log,alias}`

### Added — Integrations
- **Web search:** DuckDuckGo (zero config), Tavily, SearXNG backends
- **Telegram:** alert mode (send messages/photos/files) + chat bot with daemon
- **Scheduler:** interval/daily/cron scheduling with background daemon process
- **Browser:** Playwright-based automation (scrape, screenshot, form fill)
- **Webhooks:** Slack, Discord, and generic endpoint support
- Integration registry with status display
- Skill builder dynamically injects integration context into LLM prompts
- Planner SCHEDULE step type for recurring tasks
- Composer SCHEDULE handler with daemon hints
- 15+ CLI commands for setup, testing, and management

### Changed
- Skill metadata now includes `generation`, `lineage`, `network_evolved`, `origin` fields
- `alive init` generates agent identity and creates network directory
- Updated CLAUDE.md with full project status

### Tests
- 72 network tests, 91 integration tests
- **657 total tests, all passing**

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## [0.1.0] — 2026-03-18

### Added — Core
- CLI with typer + rich (40+ commands)
- LLM provider abstraction (Claude, OpenAI, DeepSeek, Ollama)
- Skill registry with Wilson score confidence ranking
- Skill builder with Battle Mode (two implementations compete)
- Sandbox executor (subprocess isolation, 60s timeout)
- Planner: decomposes requests into EXISTING_SKILL, NEW_SKILL, LLM_ONLY steps
- Composer: executes plans step-by-step with error recovery and synthesis
- Skill chaining: named multi-skill pipelines with scheduling
- Skill graph: relationship visualization with DOT export
- Self-model: capability tracking, gap analysis, domain classification
- Dream log: self-reflection engine
- Skill evolution: improve existing skills based on execution stats
- Skill teaching: import external Python scripts as skills
- Shell history analysis: suggest skills from command patterns
- Persistent memory: per-skill SQLite key-value store
- Skill sharing: export/import as tar.gz archives, GitHub Gist support

### Tests
- 585 tests covering all core modules
