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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。

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Prix non confirmé★ 24 Stars GitHubRegistre mis à jour · 9 oct. 2026agent-skill

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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

先由对应 QMT Skill 生成报告（复盘、盈亏等）
当日复盘：daily_trade_report.py --feishu-md 导出 reports/feishu_daily_eval.md（禁止 Agent 手写摘要）
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-review	`reports/feishu_daily_eval.md`
daily-pnl	盈亏快照	daily-pnl	`reports/feishu_daily_pnl.md`
return-analysis	涨跌分析	return-analysis	`reports/feishu_return_analysis.md`
portfolio-risk	组合风控	portfolio-risk	`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。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

lark-cli auth status 正常；已读 lark-shared + lark-doc
运行对应 QMT Skill 脚本取数
写 reports/*.md（--content 路径相对仓库根）
docs +update 或 +create（可先 --dry-run）
核对云文档标题与 H1 一致
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

Voir la source ↗

Métadonnées du fichier

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。

Voir le texte original

---
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

Examiner la source

Prix et coûts d’utilisation

Obtenir le skill: Prix non confirmé
L’utiliser: Prérequis non confirmés. Consultez les frais d’agent, d’API et de services à la source.
Licence: MIT
Prix non confirmé: Le prix n’est pas confirmé. Les liens existants vers les sources et l’installation restent disponibles.

Gratuit à obtenir ne signifie pas gratuit à utiliser. Le prix ne constitue pas une évaluation de sécurité. Soumettre un prix →

Source du skill enregistrée

Un chemin vers les instructions est enregistré. Cela ne constitue pas un test, une garantie de sécurité ou de compatibilité.

Réviser avant installation: Éviter l’installation automatique

Licence: 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
L’approbation de revue IA est absente
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

Ouvrir l’audit complet

Les outils sont des indications de métadonnées, pas une compatibilité testée. Les prompts sont des suggestions.

Commencer par une petite tâche

1Lisez la source et confirmez entrées, résultats, dépendances et permissions.
2Demandez un plan à l’agent. Approuvez la configuration et les coûts avant un test isolé.
3Vérifiez résultats et fichiers modifiés. Signalez uniquement ce qui a été exécuté et conservez la révision source.

Vérifiez les dépendances, clés API et frais externes dans la source. Un dépôt public ne rend pas tous les services gratuits.

Source et conseils d’utilisation

RépertoriéContrôle statique

Métadonnées et examens sont indicatifs. Popularité, découverte et exécution réussie sont des faits distincts.

Dépôt source: atorber/qmt-trading-skill
Licence: MIT
Version: Unknown
Dernier push GitHub: 22 sept. 2026
Registre mis à jour: 9 oct. 2026
Chemin des instructions: skills/qmt-bridge-feishu-doc/SKILL.md @ 04e8bee0c525

Version déclarée dans le registre ; vérifiez les versions de la source.

Qualité

55/100

Prometteur

Confiance

59/100

Do not auto-install

Audit

71/100

Revue nécessaire

Ouvrir l’audit complet Voir le rapport d’évaluation

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
L’approbation de revue IA est absente
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: —
Résultats: —

Copier ne signifie pas installer. Les compteurs nécessitent un rapport de réussite et ne garantissent pas la qualité globale.

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L’API Registry fournit les signaux de décision, confiance, audit, cas d’usage et installation sans analyser l’interface.

Ouvrir l’API d’installation Format texte LLM Ouvrir Manifest Plan de résolution auto

Plus de détails

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    ],
    "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"
  }
}

Pour le créateur

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Cette fiche a été indexée à partir de sources publiques et n’est pas marquée officielle tant qu’une revendication de mainteneur n’est pas approuvée.

Créateur: atorber
Source: atorber/qmt-trading-skill
Indexé par: Index communautaire OpenAgentSkill

L’attribution renvoie au dépôt public ou au profil du créateur. Les créateurs peuvent revendiquer la fiche pour mettre à jour les signaux de propriété.

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