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finskills-portfolio-manager芬技能投资组合经理

Agent Skill

finskills-portfolio-manager 用于补充运维相关能力,适合在 OpenClaw 中需要让 Agent 承接运维相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:finskills-portfolio-manager(芬技能投资组合经理)
来源仓库:https://github.com/finskills/finskills-portfolio-manager
安装命令:
openclaw skills install finskills-portfolio-manager
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install finskills-portfolio-manager

简介

使用来自 Finskills API 的实时报价、行业分配和风险指标来监控和重新平衡多资产投资组合。

SKILL.md

name
Portfolio Manager
version
1.0.3
description
Monitor and rebalance a multi-asset portfolio using real-time quotes, sector allocation, and risk metrics from the Finskills API.
author
finskills
metadata
openclaw
requires
env
primaryEnv
FINSKILLS_API_KEY
homepage
https://github.com/finskills/portfolio-manager

Portfolio Manager

Monitor, analyze, and optimize a multi-asset US equity portfolio using live batch quotes, market summary data, and sector performance from the Finskills API. Computes real-time P&L, risk metrics, sector concentration, and generates rebalancing recommendations aligned with your target allocation.


Setup

API Key requiredRegister at https://finskills.net to get your free key. Header: X-API-Key: <your_api_key>

Get your API key: Register at https://finskills.net — free tier available, Pro plan unlocks real-time quotes, history, and financials.

When to Activate This Skill

Activate when the user:

  • Provides a list of holdings (ticker + shares or $ value) and asks for portfolio analysis
  • Asks about their portfolio's performance, sector concentration, or risk metrics
  • Wants a rebalancing recommendation
  • Asks how their portfolio compares to the S&P 500 or benchmarks
  • Asks which positions are dragging or leading performance

Required Information

Before starting, collect:

  1. Holdings list: Each entry needs ticker, shares (or current_value), and optionally cost_basis
  2. Total portfolio value (or derive from positions)
  3. Target allocation (if rebalancing is requested) — e.g., "60% equities, 30% bonds, 10% cash"
  4. Benchmark — Default is S&P 500 (SPY)

Example holdings input format:

AAPL: 50 shares @ $150 cost basis
MSFT: 30 shares @ $280 cost basis
NVDA: 20 shares @ $400 cost basis
SPY:  100 shares @ $420 cost basis

Data Retrieval — Finskills API Calls

1. Batch Quotes for All Holdings

GET https://finskills.net/v1/stocks/quotes?symbols={TICKER1,TICKER2,...}

Extract for each: price, changePercent, marketCap, volume

2. Market Summary (Benchmark)

GET https://finskills.net/v1/market/summary

Extract: S&P 500, Nasdaq, Dow Jones — current level, daily change, YTD performance

3. Sector Performance

GET https://finskills.net/v1/market/sectors

Extract: All 11 GICS sector ETF performances (1D, 1W, 1M, YTD) for context

4. Company Profile (for sector classification)

For each unique ticker not already classified:

GET https://finskills.net/v1/stocks/profile/{SYMBOL}

Extract: sector, industry (to assign sector weight in portfolio)


Analysis Workflow

Step 1 — Position Valuation

For each holding:

Current Value   = shares × current_price
Daily P&L       = shares × (current_price − prev_close_price)
Daily P&L %     = current_price / prev_close_price − 1
Total P&L       = current_value − (shares × cost_basis)    [if cost basis provided]
Total P&L %     = (current_value / (shares × cost_basis)) − 1
Portfolio Weight = current_value / total_portfolio_value

Step 2 — Portfolio-Level Metrics

Performance:

Portfolio Daily Return  = Σ (weight_i × daily_return_i)
Portfolio Total Return  = (total_current_value / total_cost_basis) − 1  [if basis known]
Best Performer (1D)     = max daily_return_i
Worst Performer (1D)    = min daily_return_i

Risk Metrics (estimate from weights and sector exposure):

  • Concentration Risk: Largest single position as % of portfolio

- > 20%: High concentration ⚠️ - > 35%: Very high concentration 🚨

  • Sector Concentration: Top sector weight

- > 40%: Sector-concentrated ⚠️

  • Beta Approximation: Weight-average of individual stock betas (if available from profile data)

- Use sector beta proxies: Tech ≈ 1.3, Utilities ≈ 0.5, Financials ≈ 1.1, Healthcare ≈ 0.7

Benchmark Comparison:

Relative Return (1D) = Portfolio Daily Return − S&P 500 Daily Return

Step 3 — Sector Allocation Analysis

Group holdings by sector (using profile data):

  • Compute actual sector weights
  • Compare to S&P 500 sector weights (approximate benchmarks):

- Technology: 29%, Healthcare: 13%, Financials: 13%, Consumer Disc: 11%, Industrials: 9%, Communication: 8%, Energy: 4%, Consumer Staples: 6%, Real Estate: 3%, Materials: 2%, Utilities: 2%

Flag overweight (> +10pp vs benchmark) and underweight (< -10pp vs benchmark) sectors.

Step 4 — Rebalancing Analysis (if requested)

Target deviation detection:

For each position:
  Target Weight = stated_target_%
  Current Weight = current_value / total_value
  Drift = Current Weight − Target Weight
  Rebalance Action = BUY/SELL if abs(Drift) > 5%
  Rebalance Quantity = abs(Drift × total_value) / current_price  [shares to trade]

Tax-aware note: Flag positions with > 1 year holding for LTCG treatment before suggesting sells.

Step 5 — Actionable Recommendations

Generate 3–5 specific recommendations:

  • Positions to trim (concentration/overweight sector)
  • Positions to add (underweight sectors relative to conviction)
  • Hedging suggestions (if portfolio Beta > 1.2 and market at all-time highs)
  • Cash deployment suggestions (if cash > 10% of target)

Output Format

╔══════════════════════════════════════════════════════╗
║      PORTFOLIO REPORT  —  {DATE}                    ║
╚══════════════════════════════════════════════════════╝

💼 PORTFOLIO SUMMARY
  Total Value:     ${total_value}
  Daily P&L:       ${daily_pnl}  ({daily_pnl_pct}%)
  Total Return:    ${total_pnl}  ({total_pnl_pct}%)  [vs. cost basis]
  vs. S&P 500 (1D): {+/- bps} bps

📋 HOLDINGS BREAKDOWN
  {Ticker}  {Shares}sh  ${price}  {weight}%  Day: {+/-}%  Total: {+/-}%
  ─────────────────────────────────────────────────────
  AAPL      50 sh       $189.40   18.4%      +1.2%       +26.3%
  MSFT      30 sh       $415.20   24.2%      -0.3%       +48.2%
  ...
  ─────────────────────────────────────────────────────
  TOTAL     —           —         100%       {port_day}% {port_total}%

  🏆 Best Today:  {ticker} +{%}
  📉 Worst Today: {ticker} -{%}

🏛️ SECTOR ALLOCATION
  Sector           Portfolio  S&P 500  Over/Under
  Technology         {%}       29%      {+/-pp}
  Healthcare         {%}       13%      {+/-pp}
  ...
  [⚠️ Any sectors > 40% or > +15pp vs benchmark]

⚠️ RISK FLAGS
  • Largest position: {ticker} at {%} [{normal/concentrated}]
  • Est. Portfolio Beta: {beta} [vs SPY]
  • {Any other flags}

📊 MARKET CONTEXT
  S&P 500:  {level}  {day_change}%  YTD: {ytd}%
  Nasdaq:   {level}  {day_change}%  YTD: {ytd}%
  {Leading sector today}: +{%}
  {Lagging sector today}: -{%}

🔄 REBALANCING RECOMMENDATIONS
  1. {Action}: {Ticker} — {rationale}
  2. {Action}: {Ticker} — {rationale}
  3. {Action}: Consider adding {sector} exposure (currently underweight {pp})

Limitations

  • Batch quote latency may be 1–15 minutes delayed depending on data source.
  • Beta estimates are approximated from sector proxies unless individual beta data is available.
  • Bond, international equity, and alternative assets are not currently covered.
  • This skill does not connect to brokerage accounts or execute trades.

适合场景

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02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

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补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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安装前确认

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