system-architecture
Align implementation and docs with the repo's 10-layer vision (docs/FINAL_SYSTEM_VISION.md) and AGENTS.md. Use when planning or reviewing cross-cutting features touching AI (Layer 5), learning (Layer
SKILL.mdagents/skills/system-architecture/SKILL.md
GitHubSystem architecture alignment
Purpose
Keep coding agents, skills, and PRs consistent with:
docs/FINAL_SYSTEM_VISION.md— canonical product and architecture vision (10 layers).AGENTS.md— enforceable module boundaries, safety defaults, and current code mapping.docs/IMPLEMENTATION_GAP.md— short vision vs implementation honesty (optional read when scoping work).
This skill does not replace reading those files.
Layer anchors (must not swap)
- Layer 5 = AI support — LLM confirmation / recommendation; never the only authority for execution.
- Layer 6 = Learning and optimization — outcome-driven improvement, shadow/diagnostic first in this repo unless explicitly extended.
Cross-cutting principles (binding with AGENTS.md)
- Strong operator observability — L9–L10 surfaces and journals should reflect what the system did and why.
- Continuous research / testnet data — prefer runs that feed journals and metrics for L6; avoid untracked “fire and forget” experiments.
- Bounded autonomy — autonomous loops stay within config, env, and operator controls; no silent background traders.
- No black-box runtime — no untraced changes to effective signals, weights, or risk; decision paths remain structured and logged where the repo already does so.
Use when
- Designing or reviewing features that span multiple packages (
market,strategies,ai,learning,risk,execution,operator_panel). - Documenting or refactoring “layers” in skills or README.
- Clarifying whether a change belongs to advisory AI (L5) vs learning (L6) vs risk (L7).
Do not use when
- Single-file trivial edits with no architectural implication.
- Replacing a full read of
FINAL_SYSTEM_VISION.mdfor detailed formulas or future data sources.
Workflow
- Read
AGENTS.md(boundaries + safety). - Skim relevant sections of
docs/FINAL_SYSTEM_VISION.mdfor the layers you touch. - Ensure the change advances the vision without violating AGENTS (paper default, risk not bypassed, AI advisory, learning not secretly trading).
- Prefer minimal diff; update skills/docs only when guidance would otherwise stay wrong.
Output
- State which layers are affected (numbers + names).
- Note vision vs current repo gap if the implementation is partial.
- Explicit safety confirmation: risk ordering, paper defaults, no live enablement.