name	quantdinger-agent-workflow
description	QuantDinger repo workflow for coding agents: layered contracts, safety boundaries, and where backend, strategies, and Docker live. Use when editing Python API, strategies, deployment, or docs/agent.

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

docs/agent/AGENT_ENVIRONMENT_DESIGN.md - SSOT for three layers: documentation contract -> command contract -> optional HTTP/MCP.
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.
docs/agent/AGENT_QUICKSTART.md - Operator/integrator walkthrough; mirrors the implemented /api/agent/v1 surface.
docs/agent/agent-openapi.json - Machine-readable contract; update it whenever you add or change an /api/agent/v1/... route.
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.

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

docs/agent/AGENT_ENVIRONMENT_DESIGN.md - SSOT for three layers: documentation contract -> command contract -> optional HTTP/MCP.

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.

docs/agent/AGENT_QUICKSTART.md - Operator/integrator walkthrough; mirrors the implemented /api/agent/v1 surface.

docs/agent/agent-openapi.json - Machine-readable contract; update it whenever you add or change an /api/agent/v1/... route.

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.

quantdinger-agent-workflow