quantdinger-agent-workflow

name	quantdinger-agent-workflow
description	>- Use when this capability is needed.

QuantDinger agent workflow

When this applies

Use this skill whenever you change code or docs under this repository as a coding agent (Cursor, Claude Code, Codex, or similar), especially:

• backend_api_python/ (Flask API, services, routes)
• Strategy / backtest / trading-adjacent logic
• docker-compose.yml, scripts/, env.example
• docs/agent/ (keep English only)

Read first

1. docs/agent/AGENT_ENVIRONMENT_DESIGN.md - SSOT for three layers: documentation contract -> command contract -> optional HTTP/MCP.
2. docs/agent/AI_INTEGRATION_DESIGN.md - How external AI agents consume QuantDinger as a product (Agent Gateway, scopes, MCP, trading safety). Read this before adding any new endpoint or tool that an AI agent might call.
3. docs/agent/AGENT_QUICKSTART.md - Operator/integrator walkthrough; mirrors the implemented /api/agent/v1 surface.
4. docs/agent/agent-openapi.json - Machine-readable contract; update it whenever you add or change an /api/agent/v1/... route.
5. docs/agent/README.md - Index of agent-facing docs.

Implemented surface (truth)

The Agent Gateway is mounted at /api/agent/v1 by app/routes/agent_v1/.

• Auth: app/utils/agent_auth.py (@agent_required(scope=...)). Tokens are hashed at rest in qd_agent_tokens; never log or persist the raw token.
• Async jobs: app/utils/agent_jobs.py writes to qd_agent_jobs; backtests and experiment pipelines submit here and clients poll /jobs/{id} or subscribe to GET /jobs/{id}/stream (SSE: snapshot / progress / ping / result). Long-running runners can opt in by adding a second positional on_progress parameter. submit_job will detect it and pipe events to live SSE subscribers AND persist the latest snapshot.
• Audit: every call (success and denial) is appended to qd_agent_audit.
• Trading: quick_trade.py enforces paper-only by default; live execution requires both paper_only=false on the token AND env AGENT_LIVE_TRADING_ENABLED=true. Do not weaken this without explicit ask.
• MCP: mcp_server/ is a thin Python wrapper over R + W + B endpoints (no trading), with three transports selected by QUANTDINGER_MCP_TRANSPORT: stdio (default, desktop IDEs), sse, and streamable-http (cloud agents / remote IDEs; also bind QUANTDINGER_MCP_HOST / QUANTDINGER_MCP_PORT). Add new tools there only after exposing the underlying capability via REST.
• Admin UI: the Vue project at QuantDinger-Vue-src/ ships Profile -> My Agent Token for every logged-in user (src/views/profile/components/ProfileAgentTokens.vue, API /api/agent/v1/me/tokens). Admins retain /agent-tokens for audit. API client lives in src/api/agent.js.

Do not treat the marketing-heavy root README.md as the only onboarding doc; use it for user install paths and link out.

Red Lines

• Never commit real secrets, production .env, API keys, or DB passwords. Use env.example patterns and placeholders in examples.
• Do not add live trading or order placement automation that bypasses human review unless explicitly requested and scoped.
• Prefer linking to docs/STRATEGY_DEV_GUIDE*.md over duplicating long strategy guide text inside agent-only docs.

Repository Anchors

Area	Path
Backend	backend_api_python/
Frontend (prebuilt UI)	frontend/
Compose stack	docker-compose.yml, scripts/
Strategy guides	docs/STRATEGY_DEV_GUIDE.md (and localized variants)

Verification

• Backend tests live in backend_api_python/tests/; run with python -m pytest tests/ -q from backend_api_python/.
• Agent Gateway tests: tests/test_agent_v1.py (token auth, scopes, rate limit, generator format).
• For human stack changes, follow the Docker Compose flow already documented in the root README.md (PowerShell or Bash).

Language

All new agent-facing prose (this skill, docs/agent/*) must be English so the same material works across locales and tools.

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Source: brokermr810/QuantDinger — distributed by TomeVault.