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qmt-bridge-feishu-doc

将 QMT Trading Skill 复盘/盈亏/分析报告同步到飞书云文档:规定云空间目录与标题命名, 通过官方 lark-cli 与 lark-doc、lark-drive、lark-shared Skill 完成(不用仓库 scripts/ 飞书脚本)。 在用户提到上传飞书、同步复盘文档、飞书云文档时使用。

Quelle prüfenAuf GitHub ansehen
Preis unbestätigt★ 24 GitHub-StarsVerzeichnis aktualisiert · 9. Okt. 2026agent-skill

Übersicht

将 QMT Trading Skill 复盘/盈亏/分析报告同步到飞书云文档:规定云空间目录与标题命名, 通过官方 lark-cli 与 lark-doc、lark-drive、lark-shared Skill 完成(不用仓库 scripts/ 飞书脚本)。 在用户提到上传飞书、同步复盘文档、飞书云文档时使用。

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QMT Trading Skill · 飞书云文档

实现状态:规程 + doc-registry.md;IO 走 lark-cli 官方 CLI

目标

  1. 先由对应 QMT Skill 生成报告(复盘、盈亏等)
  2. 当日复盘:daily_trade_report.py --feishu-md 导出 reports/feishu_daily_eval.md(禁止 Agent 手写摘要)
  3. 用 lark-doc / lark-drive(lark-cli docs +update 等)写入飞书

lark-cli 首次使用(Agent)

完整步骤见 references/lark-cli-setup.md,摘要:

npx @larksuite/cli@latest install
npx skills add larksuite/cli -y -g
lark-cli config init --new          # 链接发给用户浏览器配置
lark-cli auth login --recommend
lark-cli auth status

执行飞书写操作前 MUST 读 lark-shared;改 docx 读 lark-doc(--api-version v2);改列表标题 / 文件夹读 lark-drive。

不要使用本仓库 scripts/ 下已移除的飞书 Python 脚本;不要在本目录维护上传脚本。

云空间目录

QMT Trading Skill/
├── 每日复盘/      ← daily-eval
├── 盈亏快照/      ← daily-pnl
├── 涨跌分析/      ← return-analysis
└── 组合风控/      ← portfolio-risk

文件夹 token → .env(见 doc-registry)。

报告类型

type子目录先执行的 QMT Skill本地 Markdown
daily-eval每日复盘execution-reviewreports/feishu_daily_eval.md
daily-pnl盈亏快照daily-pnlreports/feishu_daily_pnl.md
return-analysis涨跌分析return-analysisreports/feishu_return_analysis.md
portfolio-risk组合风控portfolio-riskreports/feishu_portfolio_risk.md

doc token:reports/feishu_doc_ids.json 或 FEISHU_*_DOC_ID。

工作流:当日复盘

详见 references/workflows/daily-eval-sync.md。同步前必须先跑 --feishu-md。

放置位置

情况行为
用户未指定父文档wiki +node-create --as user --title "..."(不传 --parent-node-token)→ 个人知识库根
用户给出 wiki 父页面 URL/token加 --parent-node-token <TOKEN> 建子文档
用户要求云空间子目录docs +create --folder-token ...
覆盖已有 docdocs +update --doc DOC_TOKEN ...

勿在未指定时沿用历史对话中的父节点。父 token 可选:FEISHU_DAILY_EVAL_WIKI_PARENT_TOKEN 或 feishu_doc_ids.json 的 daily-eval-wiki-parent。

提示词示例

场景提示词
复盘上传把今日交易复盘同步到飞书文档(默认知识库根新建)
指定父页同步到飞书 wiki 父文档 <URL> 下,新建子文档
盈亏上传当日盈亏到飞书盈亏快照目录
新建在飞书每日复盘目录新建一篇今日复盘

操作规程

  1. lark-cli auth status 正常;已读 lark-shared + lark-doc
  2. 运行对应 QMT Skill 脚本取数
  3. 写 reports/*.md(--content 路径相对仓库根)
  4. docs +update 或 +create(可先 --dry-run)
  5. 核对云文档标题与 H1 一致
  6. 只上传报告,不下单

标题规范(摘要)

QMT Trading Skill 当日复盘 2026-05-21 15:30:00 — 见 doc-registry。

安全

  • 遵循 lark-cli 官方安全提示;凭证在系统密钥链,勿泄露
  • 报告含交易数据,注意云文档权限范围
Dateimetadaten
name: qmt-bridge-feishu-doc
description: >-
  将 QMT Trading Skill 复盘/盈亏/分析报告同步到飞书云文档:规定云空间目录与标题命名,
  通过官方 lark-cli 与 lark-doc、lark-drive、lark-shared Skill 完成(不用仓库 scripts/ 飞书脚本)。
  在用户提到上传飞书、同步复盘文档、飞书云文档时使用。
Originaltext anzeigen
---
name: qmt-bridge-feishu-doc
description: >-
  将 QMT Trading Skill 复盘/盈亏/分析报告同步到飞书云文档:规定云空间目录与标题命名,
  通过官方 lark-cli 与 lark-doc、lark-drive、lark-shared Skill 完成(不用仓库 scripts/ 飞书脚本)。
  在用户提到上传飞书、同步复盘文档、飞书云文档时使用。
---

# QMT Trading Skill · 飞书云文档

> **实现状态**:规程 + [doc-registry.md](references/doc-registry.md);IO 走 **[lark-cli](https://github.com/larksuite/cli)** 官方 CLI

## 目标

1. 先由对应 QMT Skill 生成报告(复盘、盈亏等)
2. **当日复盘**:`daily_trade_report.py --feishu-md` 导出 `reports/feishu_daily_eval.md`(**禁止** Agent 手写摘要)
3. 用 **lark-doc** / **lark-drive**(`lark-cli docs +update` 等)写入飞书

## lark-cli 首次使用(Agent)

完整步骤见 **[references/lark-cli-setup.md](references/lark-cli-setup.md)**,摘要:

```bash
npx @larksuite/cli@latest install
npx skills add larksuite/cli -y -g
lark-cli config init --new          # 链接发给用户浏览器配置
lark-cli auth login --recommend
lark-cli auth status
```

执行飞书写操作前 **MUST** 读 **lark-shared**;改 docx 读 **lark-doc**(`--api-version v2`);改列表标题 / 文件夹读 **lark-drive**。

**不要**使用本仓库 `scripts/` 下已移除的飞书 Python 脚本;**不要**在本目录维护上传脚本。

## 云空间目录

```
QMT Trading Skill/
├── 每日复盘/      ← daily-eval
├── 盈亏快照/      ← daily-pnl
├── 涨跌分析/      ← return-analysis
└── 组合风控/      ← portfolio-risk
```

文件夹 token → `.env`(见 doc-registry)。

## 报告类型

| type | 子目录 | 先执行的 QMT Skill | 本地 Markdown |
|------|--------|-------------------|---------------|
| daily-eval | 每日复盘 | [execution-review](../qmt-bridge-execution-review/SKILL.md) | `reports/feishu_daily_eval.md` |
| daily-pnl | 盈亏快照 | [daily-pnl](../qmt-bridge-daily-pnl/SKILL.md) | `reports/feishu_daily_pnl.md` |
| return-analysis | 涨跌分析 | [return-analysis](../qmt-bridge-return-analysis/SKILL.md) | `reports/feishu_return_analysis.md` |
| portfolio-risk | 组合风控 | [portfolio-risk](../qmt-bridge-portfolio-risk/SKILL.md) | `reports/feishu_portfolio_risk.md` |

doc token:`reports/feishu_doc_ids.json` 或 `FEISHU_*_DOC_ID`。

## 工作流:当日复盘

详见 **[references/workflows/daily-eval-sync.md](references/workflows/daily-eval-sync.md)**。同步前必须先跑 `--feishu-md`。

**放置位置**

| 情况 | 行为 |
|------|------|
| 用户**未**指定父文档 | `wiki +node-create --as user --title "..."`(**不传** `--parent-node-token`)→ **个人知识库根** |
| 用户给出 **wiki 父页面 URL/token** | 加 `--parent-node-token <TOKEN>` 建子文档 |
| 用户要求云空间子目录 | `docs +create --folder-token ...` |
| 覆盖已有 doc | `docs +update --doc DOC_TOKEN ...` |

勿在未指定时沿用历史对话中的父节点。父 token 可选:`FEISHU_DAILY_EVAL_WIKI_PARENT_TOKEN` 或 `feishu_doc_ids.json` 的 `daily-eval-wiki-parent`。

## 提示词示例

| 场景 | 提示词 |
|------|--------|
| 复盘上传 | `把今日交易复盘同步到飞书文档`(默认知识库根新建) |
| 指定父页 | `同步到飞书 wiki 父文档 <URL> 下,新建子文档` |
| 盈亏 | `上传当日盈亏到飞书盈亏快照目录` |
| 新建 | `在飞书每日复盘目录新建一篇今日复盘` |

## 操作规程

1. `lark-cli auth status` 正常;已读 **lark-shared** + **lark-doc**
2. 运行对应 QMT Skill 脚本取数
3. 写 `reports/*.md`(`--content` 路径相对仓库根)
4. `docs +update` 或 `+create`(可先 `--dry-run`)
5. 核对云文档标题与 H1 一致
6. **只上传报告,不下单**

## 标题规范(摘要)

`QMT Trading Skill 当日复盘 2026-05-21 15:30:00` — 见 doc-registry。

## 安全

- 遵循 lark-cli 官方安全提示;凭证在系统密钥链,勿泄露
- 报告含交易数据,注意云文档权限范围

Quelle prüfen

Preis und Betriebskosten

Skill beziehen
Preis unbestätigt
Ausführen
Anforderungen unbestätigt. Agenten-, API- und Dienstkosten an der Quelle prüfen.
Lizenz
MIT
Preis unbestätigt
Der Preis ist noch nicht bestätigt. Vorhandene Quell- und Installationslinks bleiben verfügbar.

Kostenloser Bezug bedeutet nicht kostenlosen Betrieb. Preise sind keine Sicherheitsbewertung. Preisinformation einreichen →

Skill-Quelle erfasst

Ein Anleitungspfad ist erfasst. Das ist kein Ausführungstest und keine Sicherheits- oder Kompatibilitätsgarantie.

Vor Installation prüfen: Automatische Installation vermeiden

Lizenz: MIT

  • Dependency or permission surface needs review
  • Permission surface may require sandboxing
  • Financial research output is not financial advice; require human review before any live investment decision
  • Low GitHub adoption signal
  • KI-Prüffreigabe fehlt
  • Financial research output is not financial advice; require human review before any live investment decision.
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • GitHub adoption: 24 GitHub stars
  • Stars/forks activity: 24 stars, 6 forks; issue activity unavailable in current metadata
  • Dependency/runtime risk: command execution surface, credential or environment access
  • Permission surface: secrets or environment access, shell or command execution
Vollständiges Audit öffnen

Tools sind Metadatenhinweise, keine getestete Kompatibilität. Prompts sind Vorschläge.

Mit einer kleinen Aufgabe beginnen

  1. 1Quelle lesen und Eingaben, Ergebnisse, Abhängigkeiten sowie Berechtigungen prüfen.
  2. 2Agent um einen Plan bitten. Einrichtung und Kosten vor einem isolierten Test genehmigen.
  3. 3Ergebnisse und geänderte Dateien prüfen. Nur tatsächliche Ausführungen melden und die Quellrevision aufbewahren.

Prüfe Abhängigkeiten, API-Schlüssel und externe Kosten in der Quelle. Öffentliche Repositories bedeuten nicht, dass alle Dienste kostenlos sind.

Quelle und Nutzungshinweise

ErfasstStatisch geprüft

Metadaten und Prüfungen dienen der Orientierung. Beliebtheit, Quellenerfassung und erfolgreiche Ausführung sind verschiedene Fakten.

Quell-Repository
atorber/qmt-trading-skill
Lizenz
MIT
Version
Unknown
Letzter GitHub-Push
22. Sept. 2026
Verzeichnis aktualisiert
9. Okt. 2026

Version aus den Verzeichnismetadaten; Releases der Quelle prüfen.

Qualität

55/100

Vielversprechend

Vertrauen

59/100

Do not auto-install

Audit

71/100

Prüfung nötig

  • Dependency or permission surface needs review
  • Permission surface may require sandboxing
  • Financial research output is not financial advice; require human review before any live investment decision
  • Low GitHub adoption signal
  • KI-Prüffreigabe fehlt
  • Financial research output is not financial advice; require human review before any live investment decision.
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • GitHub adoption: 24 GitHub stars
  • Stars/forks activity: 24 stars, 6 forks; issue activity unavailable in current metadata
  • Dependency/runtime risk: command execution surface, credential or environment access
  • Permission surface: secrets or environment access, shell or command execution
Verified installs
—
Ergebnisse
—

Kopieren ist keine Installation. Zahlen benötigen eine Erfolgsmeldung und garantieren keine allgemeine Qualität.

Agent-Zugang

Die Registry API stellt Entscheidungs-, Vertrauens-, Audit-, Use-Case- und Installationssignale ohne UI-Scraping bereit.

Weitere Details
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        "id": "claude-code",
        "label": "Claude Code",
        "kind": "agent-prompt",
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        "id": "cursor",
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      "install_success_rate": null,
      "risk_blocked": 0,
      "setup_required": 0,
      "avg_output_quality": null,
      "production_outcomes": 0,
      "last_outcome_at": null,
      "label": "No agent outcome data yet"
    },
    "auto_install": {
      "allowed": false,
      "sandbox_required": true,
      "reason": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
    },
    "best_for": [
      "automation",
      "agent-skill"
    ],
    "known_risks": [
      "AI review approval is missing",
      "Financial research output is not financial advice; require human review before any live investment decision.",
      "Low GitHub adoption signal",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "GitHub adoption: 24 GitHub stars",
      "Stars/forks activity: 24 stars, 6 forks; issue activity unavailable in current metadata",
      "Dependency/runtime risk: command execution surface, credential or environment access"
    ]
  },
  "agent_proven": {
    "version": "agent-proven-v1",
    "score": 0,
    "tier": "unproven",
    "label": "Needs first agent run",
    "summary": "No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.",
    "metrics": {
      "totalOutcomes": 0,
      "successfulOutcomes": 0,
      "failedOutcomes": 0,
      "installAttempts": 0,
      "installSuccessRate": null,
      "successRate": null,
      "recentSuccessRate": null,
      "recentFailureRate": null,
      "riskBlocked": 0,
      "setupRequired": 0,
      "notRelevant": 0,
      "avgOutputQuality": null,
      "avgTimeToUsefulMs": null,
      "productionOutcomes": 0,
      "humanReviewRequired": 0,
      "uniqueAgents": 0,
      "lastOutcomeAt": null
    },
    "signals": [],
    "penalties": [
      "No real agent outcome evidence yet"
    ]
  },
  "audit": {
    "score": 71,
    "risk_level": "needs_review",
    "risk_label": "Needs review",
    "warnings": [
      "Dependency or permission surface needs review",
      "Permission surface may require sandboxing",
      "Financial research output is not financial advice; require human review before any live investment decision",
      "Low GitHub adoption signal",
      "AI review approval is missing",
      "Financial research output is not financial advice; require human review before any live investment decision.",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution"
    ]
  },
  "safety_gate": {
    "tier": "blocked",
    "label": "Blocked for auto-install",
    "auto_install_policy": "block",
    "auto_install_allowed": false,
    "human_review_required": true,
    "blocked": true,
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
  },
  "quality": {
    "score": 55,
    "label": "Promising"
  },
  "supply": {
    "track": "Finance and quant workflows",
    "scenario": "Finance and quant",
    "maintenance": "21d since push",
    "risk": "Needs review"
  },
  "alternative_skills": [],
  "do_not_use_when": [
    "teams that need a vendor-supported SLA",
    "production agents without a repository review",
    "Low GitHub adoption signal",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "Financial research output is not financial advice; require human review before any live investment decision",
    "AI review approval is missing"
  ],
  "agent_contract": {
    "task_input": "Use qmt-bridge-feishu-doc in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 67/100 Manual review",
      "Audit: 71/100 Needs review",
      "Safety: 31/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "atorber-qmt-bridge-feishu-doc (qmt-bridge-feishu-doc)",
      "install_command": "npx skills add atorber/qmt-trading-skill --skill qmt-bridge-feishu-doc",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "atorber-qmt-bridge-feishu-doc",
      "task": "Use qmt-bridge-feishu-doc in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/atorber-qmt-bridge-feishu-doc",
    "api": "https://www.openagentskill.com/api/agent/skills/atorber-qmt-bridge-feishu-doc",
    "audit": "https://www.openagentskill.com/skills/atorber-qmt-bridge-feishu-doc/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=atorber-qmt-bridge-feishu-doc&task=Use%20qmt-bridge-feishu-doc%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20qmt-bridge-feishu-doc%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20qmt-bridge-feishu-doc%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/atorber-qmt-bridge-feishu-doc/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/atorber-qmt-bridge-feishu-doc"
  }
}

Für Ersteller

Quelle des Eintrags

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Ersteller
atorber
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