通过 QMT Bridge 做板块与主题研究:成分股、板块内涨跌排序、指数权重。 在用户提到板块轮动、主题、行业强弱、成分股排名时使用。只读。
Scanned 9/2/2026
Install to Claude Code
npx -y skills add Serennity007/awesome-stock-quant-skills --skill qmt-bridge-sector-theme --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Qmt Bridge Sector Theme?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/serennity007-qmt-bridge-sector-theme)More formats (shields.io, HTML) on the badges page.
---
name: qmt-bridge-sector-theme
description: >-
通过 QMT Bridge 做板块与主题研究:成分股、板块内涨跌排序、指数权重。
在用户提到板块轮动、主题、行业强弱、成分股排名时使用。只读。
---
# QMT Trading Skill · 板块主题
> **实现状态**:✅ `sector_rank.py`
## 目标
从**板块 → 成分 → 强弱排序**形成观察池,服务主题投资与行业比较框架。
## 脚本
| 脚本 | 作用 |
|------|------|
| `scripts/sector_rank.py` | `--list-sectors` 列出板块;`--sector` 排序 |
### 有效板块名
须以 `--list-sectors` 为准。实测常用:`沪深A股`、`上证A股`、`深证A股`、`创业板`、`科创板`。
**注意**:`中证500` 等名称可能无效(返回空成分)。
### 性能
大板块默认仅扫描前 **800** 只成分(`--max-scan`);可用 `--sample` 随机抽样。
## 主要 API
| 方法 | 路径 | 说明 |
|------|------|------|
| GET | `/api/sector/list` | 板块列表 |
| GET | `/api/sector/stocks` | 成分股 |
| GET | `/api/sector/info` | 板块元数据 |
| GET | `/api/instrument/index_weight` | 指数权重 |
| GET | `/api/market/full_tick` | 成分行情 |
## 规程(规划)
1. `sector/list` 或用户指定板块名
2. `sector/stocks` 取成分
3. 批量 `full_tick`,按涨跌幅排序输出 Top N(含 `batch_stock_name` 中文名)
4. **仅观察池,不自动下单**
## 安全
- 只读
## 参考
- [qmt-bridge-market-watch](../qmt-bridge-market-watch/SKILL.md) · `[REST API](https://atorber.github.io/qmt-bridge/rest-api/)`
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!
Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...
Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.
**Complete production-ready guide for Google Gemini embeddings API** This skill provides comprehensive coverage of the `gemini-embedding-001` model for generating text embeddings, including SDK usage, REST API patterns, batch processing, RAG integration with Cloudflare Vectorize, and advanced use cases like semantic search and document clustering. ---
Use when a repo needs CodeGraph plus ast-grep for Codex MCP setup, exploration, impact analysis, structural search, or safe refactor planning.
Interview, source-challenge, verify, save, and ADR-gate fuzzy coding requests into Codex-ready implementation specs. Use when a feature, bugfix, refactor, migration, repo-wide change, or architecture task needs user-verified requirements, source-backed decisions, durable architecture decisions, acceptance criteria, validation commands, rollout notes, saved spec/ADR files, and a Codex execution prompt. Do not use when already fully specified or when the user wants direct implementation now.