22 self-learning agents with memory, security review, code quality, deployment validation, and infrastructure…
EquilateralAgents Open Core
以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →
**22 self-learning AI agents. Build institutional knowledge that compounds over time. MIT licensed.**
Transform your AI coding assistant into a learning system that gets smarter with every mistake you make (and prevents you from making it again).
---
What's New in v3.1.0
YAML Standards Format (v3.0.0 - Breaking Change)
All standards now use YAML format instead of markdown. This enables machine-readable standards that agents consume directly:
StandardsLoader (v3.0.0)
New core utility that loads YAML standards from a three-layer directory hierarchy:
**Three layers (later overrides earlier):**
1. .standards/yaml/ - Official open standards (submodule)
2. .standards-community/ - Community-contributed patterns (submodule)
3. .standards-local/ - Your team's conventions (git-ignored)
Bundled Project/Object Skill (v3.1.0)
Session memory and standards injection included by default. Closes the loop between YAML standards on disk and enforcement in every AI session:
1. **On session start**: Reads ~/.project-object/{project}/context.md and injects prior session context
2. **Standards loading**: Scans .standards/yaml/*.yaml, extracts rules, injects as [REQUIRE]/[AVOID]/[PREFER] directives
3. **On session end**: Harvests new decisions, patterns, and corrections from the transcript
4. **Cross-platform sync**: Context syncs to Claude Code, Cursor, Codex, Windsurf via project-object sync
Migration from v2.x
- Rename .standards-local/*.md files to .yaml and convert to YAML schema
- StandardsContributor now generates .yaml output
- Knowledge harvest reports output .yaml instead of .md
- See CHANGELOG.md for complete migration details
---
Why EquilateralAgents?
The Problem: Codebases Don't Learn
Traditional development:
- ❌ Same security bugs discovered 3+ times
- ❌ N+1 query performance issues in every new feature
- ❌ Production incidents from patterns you've seen before
- ❌ New developers repeat mistakes the team already solved
- ❌ No institutional memory - knowledge lives in people's heads
The Solution: A Learning System
EquilateralAgents creates a feedback loop:
**Result:** Your codebase gets smarter over time. Mistakes happen once, not repeatedly.
---
Perfect For
🌱 Greenfield Projects
**Start right from day 1:**
- Security scanning before first commit
- Quality gates before bad patterns take root
- Document decisions as you make them
- Build standards library alongside code
**Example journey:**
- **Week 1**: Run security/quality workflows, create first standards
- **Month 1**: 10+ standards covering your specific domain
- **Month 3**: New feature? Check standards first. AI references them automatically.
🏗️ Brownfield Codebases
**Fix systematically, not randomly:**
- Agents identify patterns across entire codebase
- Document each fix as a standard (prevent recurrence)
- Gradually eliminate entire classes of bugs
- Track progress: incidents per month going down
**Example journey:**
- **Week 1**: Security scan finds 50 issues. Fix 10, document pattern.
- **Month 2**: Similar issue caught by agent during PR. Standard working.
- **Month 6**: That entire class of bugs eliminated from codebase.
**Real results:**
- Production incidents: 8/quarter → 1/quarter (87% reduction)
- Debug time: 4 hours/incident → 0 (caught in PR review)
- ROI: One prevented outage pays for entire year of standards work
---
Quick Start
Installation
No database setup. No API keys. No configuration files. Works immediately.
First Week Checklist
- [ ] **Day 1**: Run security and quality workflows on your codebase
- [ ] **Day 2**: Review .equilateral/workflow-history.json - what did agents find?
- [ ] **Day 3**: Copy .standards-local-template/ to .standards-local/
- [ ] **Day 4**: Create your first standard from most painful issue agents found
- [ ] **Day 5**: Update .claude/CLAUDE.md to reference your new standard
See BUILDING_YOUR_STANDARDS.md for complete Week 1 → Year 3 roadmap.
---
What's Included
22 Production-Ready Agents
**Infrastructure Core (3)**
- AgentClassifier - Task routing and complexity analysis
- AgentMemoryManager - Context and state management
- AgentFactoryAgent - Self-bootstrapping agent generation
**Development (6)**
- CodeAnalyzerAgent - Static analysis and metrics
- CodeGeneratorAgent - Pattern-based code generation