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SKL — Structured Knowledge Layer

Stop AI agents from breaking your architecture without you noticing. A coordination layer for repos with multiple LLM coding agents.

Is this for you?

SKL is worth trying if you are running two or more AI coding agents on the same repo and have been surprised by what one of them changed, or want to know when agents make architectural decisions without asking.

SKL is probably not worth it if you use one agent at a time, review all agent output before it reaches your repo, or your codebase is small enough to hold in one context window.

Quick start

  1. Install the VS Code extension
  2. Run SKL: Init (Phase 0) from the command palette
  3. Set export SKL_AGENT_ID=Agent-1 in your agent's terminal
  4. Push a branch

You will see what your agent changed, what risk signals fired, and whether it touched files outside its expected scope — without configuring anything else. When you are ready for scope enforcement, RFCs, and the full governance layer: run SKL: Upgrade to Full SKL.

CLI alternative:

npm install -g @skl/cli
skl init
skl status

How it works

SKL is a Git hook plus a shared state file. When an agent pushes code, the hook records what changed, runs static analysis to flag risk signals, and checks whether the change crosses scope boundaries. You see the activity in plain language. If a change is architectural, an RFC is generated and the merge is blocked until you resolve it. If two agents make conflicting assumptions, SKL surfaces the conflict before either change lands.

Phase 0 vs Full SKL

Feature Phase 0 Full SKL
Activity logging
Risk signals on push
Scope definitions required
Scope enforcement on push
RFC gate for architectural changes
Orchestrator review session
Human digest review
Queue max 50 Configurable

Known limitations

  • Import scanning is static only — dynamic imports are not detected
  • Scope definition quality is load-bearing — a poorly defined scope produces false confidence in enforcement
  • The Orchestrator requires an LLM (uses your existing Copilot model) and degrades to template fallbacks if none is available
  • Full SKL adds review overhead — this is intentional, not a bug
  • Not suitable for deep refactors, framework migrations, or cross-cutting changes where the correct scope is unknowable until implementation is underway

Contributing

SKL is in active development. See PLAN.md for the full build history and SPEC.md for the v1.4 reference specification that this extension implements.

Issues and pull requests welcome. Please read PLAN.md before contributing to understand the architecture and constraints.

A VS Code extension implementing the SKL v1.4 coordination protocol for small concurrent LLM agent teams.

SKL makes parallelism debuggable. It is not a safety system. It is a fail-stop coordination layer with bounded damage and explicit uncertainty.

Status

Stage Description Status
1 Data layer, schemas, initialization ✅ Complete
2 Enforcement hook, Queue panel ✅ Complete
3 Orchestrator 🔄 In progress
4 CI integration, acceptance criteria ⏳ Planned

Specification

The full SKL v1.4 reference specification is in SPEC.md.

Development

Built using spec-driven development with a single Copilot agent. See PLAN.md for the staged build plan.

Contributing

This project is in early development. Contributions are welcome once Stage 3 is complete. Check back soon.

About

SKL guarantees that coordination-relevant uncertainty, assumptions, and cross-scope dependencies cannot propagate implicitly. It is not a safety system. It is a fail-stop coordination system with bounded damage and explicit uncertainty.

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