Agent skill

Barchart

Quotes, fundamentals, insider, analyst ratings, earnings estimates, financial summary, income/balance/cashflow detail y company profile (delayed 15-20min).

MITAuto-check passedBusiness, Finance & HR

Install Barchart

skills CLI

$ npx skills add gauss314/skills --skill barchart -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install gauss314/skills barchart --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/gauss314/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/barchart .claude/skills/barchart && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "barchart" agent skill from https://github.com/gauss314/skills/tree/main/skills/barchart into .claude/skills/barchart/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "barchart", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/gauss314/skills/tree/main/skills/barchart

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add gauss314/skills --skill barchart -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install gauss314/skills barchart --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/gauss314/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/barchart .agents/skills/barchart && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "barchart" agent skill from https://github.com/gauss314/skills/tree/main/skills/barchart into .agents/skills/barchart/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "barchart", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add gauss314/skills --skill barchart -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install gauss314/skills barchart --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/gauss314/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/barchart .cursor/skills/barchart && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "barchart" agent skill from https://github.com/gauss314/skills/tree/main/skills/barchart into .cursor/skills/barchart/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "barchart", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/gauss314/skills.git --path skills/barchart

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add gauss314/skills --skill barchart -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install gauss314/skills barchart --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/gauss314/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/barchart .gemini/skills/barchart && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "barchart" agent skill from https://github.com/gauss314/skills/tree/main/skills/barchart into .gemini/skills/barchart/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "barchart", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install gauss314/skills barchart

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add gauss314/skills --skill barchart -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/gauss314/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/barchart .github/skills/barchart && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "barchart" agent skill from https://github.com/gauss314/skills/tree/main/skills/barchart into .github/skills/barchart/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "barchart", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add gauss314/skills --skill barchart -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install gauss314/skills barchart --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/gauss314/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/barchart .opencode/skills/barchart && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "barchart" agent skill from https://github.com/gauss314/skills/tree/main/skills/barchart into .opencode/skills/barchart/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "barchart", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: barchart
GitHub stars: 248
Token cost: ~5.4k tokens
SKILL.md length: 1,204 words
Files: 4 (incl. scripts, references)
Skills in repo: 32
Repo updated: Jun 14, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Quotes, fundamentals, insider, analyst ratings, earnings estimates, financial summary, income/balance/cashflow detail y company profile (delayed 15-20min).

Works in 2 steps: Extrae JSON del atributo… → Extrae pares Label + Value para…
Tasks that involve Architecture decision records
SKILL.md covers ⚠️ Datos clave, Instalación, Scripts and Uso rápido, plus 4 more sections
Runs Python scripts from its folder; calls pip; reaches barchart.com and gfgsa.com

What it does

Barchart is an agent skill from gauss314/skills. Quotes, fundamentals, insider, analyst ratings, earnings estimates, financial summary, income/balance/cashflow detail y company profile (delayed 15-20min). 30K+ stocks US y ADRs globales. Sin API key.

Its SKILL.md is about 5.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/API.md`, `references/REFERENCE.md` and `scripts/fetch_barchart.py`).

It sits in Business, Finance & HR, covering Architecture decision records, Financial analysis and Web scraping. The repository describes itself as: Financial market data consumption skills for claude code and AI agents. The licence is MIT.

When your agent uses it

Tasks that involve Architecture decision records
Tasks that involve Financial analysis
Tasks that involve Web scraping

Example prompts

“/barchart”

Requirements

Python 3

Workflow steps

2 steps, taken from the first numbered list in SKILL.md.

Extrae JSON del atributo data-ng-init='init({...})' (symbol, lastPrice, bid/ask, exchange, tradeTime)
Extrae pares Label + Value para fundamentals

What it can do on your machine

Read from SKILL.md and the folder at commit 5156f81. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
- pip
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
- barchart.com
- gfgsa.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Barchart loads about 5.4k tokens when it runs, and up to ~13k if it reads all its reference files. Until then it costs about 52 tokens; SKILL.md has 1,204 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~52
When it runs · the whole SKILL.md, loaded when a task matches: ~5.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~13k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from gauss314/skills at commit 5156f81, republished under its MIT licence (© gauss314). 1,204 words, ~5,380 tokens.

Download SKILL.mdSave it as .claude/skills/barchart/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.

name: barchart
description: Quotes, fundamentals, insider, analyst ratings, earnings estimates, financial summary, income/balance/cashflow detail y company profile (delayed 15-20min). 30K+ stocks US y ADRs globales. Sin API key.
license: MIT

Barchart Scraper

Extrae datos de Barchart mediante scraping HTML. Sin bs4, sin lxml, sin API key.

⚠️ Datos clave

Concepto	Respuesta
Tipo de datos	Quotes + fundamentals + insider + analyst ratings + earnings estimates + financial summary + income/balance/cashflow detail + company profile
Latencia	❌ Delayed 15-20 min (exchange delay estándar). Futuros: 10 min. No es tiempo real
Cobertura	~30,000+ símbolos US: NYSE, NASDAQ, AMEX, OTC-US. ADRs globales incluidos (GGAL, BABA, SUPV, etc.)
Requiere registro/API key	No
Dependencias	Solo `pip install requests`
Método	Scraping de HTML estático. Barchart usa AngularJS — datos renderizados client-side no disponibles

Instalación

bash

pip install requests

Scripts

Script	Descripción
`fetch_barchart.py`	Scraper: quote + fundamentals + insider + analysts + earnings estimates + income/balance/cashflow detail + company profile

Uso rápido

bash

# Quote + fundamentals (27 campos) — sin flags extra
py fetch_barchart.py AAPL
py fetch_barchart.py AAPL,MSFT,GGAL         # Multi-ticker

# Insider summary (--insider)
py fetch_barchart.py AAPL --insider

# Analyst ratings (--analysts)
py fetch_barchart.py AAPL --analysts

# Earnings estimates (--estimates)
py fetch_barchart.py AAPL --estimates

# Financial summary annual (--financials)
py fetch_barchart.py GGAL --financials

# Financial summary quarterly (--financials quarterly)
py fetch_barchart.py GGAL --financials quarterly

# Income statement detail (--income)
py fetch_barchart.py GGAL --income                    # trimestral (default)
py fetch_barchart.py GGAL --income annual

# Balance sheet detail (--balance)
py fetch_barchart.py GGAL --balance                    # trimestral (default)
py fetch_barchart.py GGAL --balance annual

# Cash flow detail (--cashflow)
py fetch_barchart.py GGAL --cashflow                   # trimestral (default)
py fetch_barchart.py GGAL --cashflow annual

# Company profile (--profile)
py fetch_barchart.py GGAL --profile

# Combinar flags
py fetch_barchart.py GGAL --insider --analysts --estimates --income --balance --cashflow

# Output
py fetch_barchart.py AAPL -o aapl.json      # Guardar JSON
py fetch_barchart.py AAPL -q                # JSON a stdout

Output real por flag

`py fetch_barchart.py AAPL` (quote + fundamentals)

  ticker: AAPL
  symbol: AAPL
  name: Apple Inc
  lastPrice: 310.26
  netChange: -4.94
  percentChange: -1.57%
  bid: 313.88
  ask: 313.97
  exchange: NASDAQ
  tradeTime: 06/03/26
  marketCap: 4,629,454,720          # en $K (dividir /1000)
  sharesOutstanding: 14,687,355      # en K
  annualSales: 416,161 M
  annualIncome: 112,010 M
  ebit: 147,366 M
  ebitda: 159,064 M
  beta: 1.09
  priceSales: 10.81
  priceCashFlow: 36.59
  priceBook: 42.25
  peRatio: 37.04
  eps: 8.27
  mostRecentEarnings: $2.01 on 04/30/26
  nextEarningsDate: 07/30/26
  dividend: 1.08 (0.35%)             # monto anual + yield
  mostRecentDividend: 0.270 on 05/11/26

`py fetch_barchart.py GGAL` (mismos campos para ADR)

  ticker: GGAL
  symbol: GGAL
  name: Grupo Fin Galicia ADR
  lastPrice: 48.33
  netChange: -2.00
  percentChange: -3.97%
  bid: 47.15 / ask: 49.99
  exchange: NASDAQ
  marketCap: 8,084,256 $K
  sharesOutstanding: 160,625 K
  annualSales: 10,559 M
  annualIncome: 170,020 K            # utilidad negativa
  ebit: -1,178 M
  ebitda: -934 M
  beta: 1.32
  priceSales: 0.78
  priceBook: 1.37
  peRatio: 0.00
  eps: 2.27
  dividend: 4.86 (9.50%)
  nextEarningsDate: 08/25/26

`--insider` (agrega)

  --- insider ---
  summaryLast3M:
    buys: 0
    buyShares: 0
    sells: 6
    sellShares: 397759

Qué significa: Últimos 3 meses hubo 0 compras y 6 ventas por 397,759 acciones por parte de insiders de la compañía.

`--analysts` (agrega)

  --- analysts ---
  current:     Moderate Buy (4.12) - 42 analysts
  1_mth_ago:   Moderate Buy (4.12) - 42 analysts
  2_mths_ago:  Moderate Buy (4.07) - 42 analysts
  3_mths_ago:  Moderate Buy (4.07) - 42 analysts

Qué significa: Rating actual = Moderate Buy con valor 4.12/5 basado en 42 analistas. La escala va de 1 (Strong Sell) a 5 (Strong Buy). Se muestra también el histórico de los últimos 3 meses.

`--estimates` (agrega)

  --- earnings estimates ---
  Average Earnings Estimate: $0.82 | $1.11 | $3.69 | $6.42
  Number of Estimates: 3 | 2 | 3 | 3
  High Estimate: $1.02 | $1.30 | $4.45 | $8.12
  Low Estimate: $0.69 | $0.92 | $3.29 | $5.21
  Prior Year: $0.94 | $0.08 | N/A | $3.69
  Growth Rate Est. (yoy): -12.77% | +1,287.50% | -99.63% | +73.98%

Columnas de la tabla: Current Qtr (06/2026) | Next Qtr (09/2026) | Fiscal Yr (12/2026) | Fiscal Yr (12/2027)

Qué significa:

Average Earnings Estimate = estimación de EPS promedio de los analistas
Number of Estimates = cuántos analistas dieron estimación para ese período
High/Low Estimate = estimación más optimista y más pesimista
Prior Year = EPS reportado en el mismo período del año anterior
Growth Rate Est. = crecimiento estimado vs año anterior

`--financials` annual (agrega)

  --- financial summary (annual) ---

  incomeStatement:
    Periods: 12-2025 | 12-2024 | 12-2023 | 12-2022 | 12-2021
    Sales: $10.56B | $11.64B | $24.99B | $9.99B | $5.11B
    Net Income: $170.02M | $1.79B | $1.28B | $374.52M | $326.49M

  balanceSheet:
    Periods: 12-2025 | 12-2024 | 12-2023 | 12-2022 | 12-2021
    Assets: $36.54B | $35.77B | $38.82B | $25.96B | $17.62B
    Liabilities: $30.33B | $29.10B | $31.16B | $21.27B | $14.42B

  cashFlow:
    Periods: 12-2025 | 12-2024 | 12-2023 | 12-2022 | 12-2021
    Cash (Operating): $-1.28B | $3.85B | $6.34B | $4.47B | $2.97B
    Net Cash Flow: $423.52M | $320.47M | $-3.28B | $588.02M | $736.72M

Qué significa: Income statement con Sales y Net Income de los últimos 5 años, Balance Sheet con Assets y Liabilities, Cash Flow con Operating Cash Flow y Net Cash Flow. Cada valor está formateado en B (billones) o M (millones). Los períodos son MM-YYYY.

`--financials quarterly` (agrega)

  --- financial summary (quarterly) ---

  incomeStatement:
    Periods: 03-2026 | 09-2025 | 06-2025 | 03-2025 | 12-2024
    Sales: $672.00M | $409.98M | $2.24B | $2.18B | $8.58B
    Net Income: $46.54M | $-70.17M | $150.71M | $146.32M | $846.01M

  balanceSheet:
    Periods: 03-2026 | 09-2025 | 06-2025 | 03-2025 | 12-2024
    Assets: $31.61B | $36.54B | $33.60B | $31.33B | $35.77B
    Liabilities: $25.60B | $30.33B | $27.92B | $25.26B | $29.10B

  cashFlow:
    Periods: 03-2026 | 09-2025 | 06-2025 | 03-2025 | 12-2024
    Cash (Operating): $-1.28B | $-966.19M | $3.85B | $5.32B | $0.00
    Net Cash Flow: $423.52M | $-1.16B | $320.47M | $1.14B | $0.00

Qué significa: Mismos campos que annual pero para los últimos 5 trimestres en lugar de años.

`--income quarterly` (agrega income statement detallado)

  --- income statement detail (quarterly) ---
    Periods: 09-2025 | 03-2025 | 12-2024 | 09-2024 | 06-2024
    Interest Income: N/A | 1,590,672 | 7,624,088 | 1,444,576 | N/A
    Interest Expense: 0 | 628,468 | 2,797,842 | 606,029 | 0
    Interest Income (Net of Interest Expense): 996,333 | 962,204 | 1,774,389 | 838,547 | 1,400,136
    Non-Interest Income: 409,984 | 589,955 | 959,292 | 576,923 | 526,451
    Sales: 1,406,317 | 1,552,158 | 2,997,404 | 1,415,470 | 1,926,588
    Credit Losses Provision: N/A | N/A | N/A | N/A | 160,058
    Non Interest Expenses: 1,545,414 | 1,340,467 | 2,005,786 | 1,132,053 | 1,074,184
    Pre-tax Income: -139,097 | 211,692 | 991,619 | 283,417 | 692,346
    Income Tax: -68,924 | 65,327 | 145,681 | 98,683 | 242,396
    Other Income: -139,097 | 840,160 | 3,789,461 | 889,446 | 692,346
    Net Income: $-70,168 | $146,321 | $846,011 | $184,766 | $449,884
    EPS Basic Continuous Ops: -0.44 | 0.92 | 4.62 | 1.25 | 3.05
    EPS Basic Total Ops: -0.44 | 0.92 | 5.67 | 1.25 | 3.05
    EPS Diluted Continuous Ops: -0.44 | 0.92 | 4.62 | 1.25 | 3.05
    EPS Diluted Total Ops: -0.44 | 0.92 | 5.67 | 1.25 | 3.05
    EPS Diluted Before Non-Recurring Items: 0.08 | 0.96 | N/A | N/A | N/A
    EBITDA(a): $N/A | $N/A | $N/A | $N/A | $N/A

Con --income annual cambian los períodos a 12-YYYY y los valores son anuales.

`--balance quarterly` (agrega balance sheet detallado)

  --- balance sheet detail (quarterly) ---
    Periods: 09-2025 | 03-2025 | 12-2024 | 09-2024 | 06-2024
    Assets:
    Cash & Cash Equivalents: 6,955,327 | 5,545,430 | 7,419,325 | 7,422,673 | 2,853,684
    Securities And Investments: 676,711 | 6,598,840 | 8,225,726 | 6,138,255 | 1,748,708
    Loans Gross: 17,647,550 | 15,687,540 | 16,561,370 | 10,078,030 | 7,070,364
    PPE Net: 936,089 | 989,632 | 1,095,073 | 810,412 | 720,216
    Total Assets: $33,596,770 | $31,332,270 | $35,769,780 | $25,272,940 | $19,191,830
    Total deposits: 19,632,510 | 17,298,760 | 20,497,760 | 15,073,540 | 9,613,379
    Long Term Debt: N/A | 1,421,175 | 1,110,457 | 507,279 | N/A
    Total Liabilities: $27,922,710 | $25,256,920 | $29,099,660 | $20,389,730 | $15,007,280
    Retained earnings: N/A | 558,626 | 464,154 | -172,847 | N/A
    Total Liabilities And Equity: $33,596,766 | $31,332,267 | $35,769,779 | $25,272,935 | $19,191,833

`--cashflow quarterly` (agrega cash flow detallado)

  --- cash flow detail (quarterly) ---
    Periods: 09-2025 | 03-2025 | 12-2024 | 09-2024 | 06-2024
    Net Income: N/A | 211,692 | 2,432,345 | 1,610,563 | N/A
    Depreciation Amortization: N/A | 55,824 | 206,874 | 125,586 | N/A
    Operating Cash Flow: $N/A | $-966,190 | $3,853,060 | $5,324,640 | $N/A
    Investing Cash Flow: $N/A | $-65,007 | $951,697 | $-142,836 | $N/A
    Financing Cash Flow: $N/A | $147,569 | $454,877 | $-490,960 | $N/A
    End Cash Position: N/A | 6,077,983 | 8,147,057 | 8,384,714 | N/A
    Net Cash Flow: $N/A | $-1,158,989 | $320,472 | $1,140,003 | $N/A
    Free Cash Flow: 0 | -1,056,768 | 3,616,886 | 5,176,481 | 0

`--profile` (agrega company profile + key statistics)

  --- profile ---
    Name: Grupo Fin Galicia ADR
    Address: TTE. GRAL. JUAN D. PERON 430 25TH FLOOR BUENOS AIRES C1 CP1038AAJ ARG
    Website: http://www.gfgsa.com
    Employees: 10,079
    Phone: 54-11-4343-7528
    Fax: 114-331-9183
    Sector: Finance
    Industries: SIC-6029 Commercial Banks, NEC, Banks - Foreign, Indices Nasdaq Composite
    Description: Grupo Financiero Galicia SA. is involved in the Financial Services Industry...

    --- overview ---
      Market Capitalization, $K: 8,084,256
      Enterprise Value, $K: 2,012,866
      Shares Outstanding, K: 160,625
      Float, K: 160,625
      % Float: 100.00%
      Short Interest, K: 6,552
      Short Float: 4.08%
      Days to Cover: 6.72
      Short Volume Ratio: 0.53
      % of Institutional Shareholders: 0.00%

    --- financials ---
      Annual Sales, $: 10,559 M
      Annual Net Income, $: 170,020 K
      Last Quarter Sales, $: 672,000 K
      Last Quarter Net Income, $: 46,540 K
      EBIT, $: -1,178 M
      EBITDA, $: -934,100 K

    --- growth ---
      1-Year Return: -14.61%
      3-Year Return: 226.33%
      5-Year Return: 387.69%
      5-Year Revenue Growth: 141.77%
      5-Year Earnings Growth: -100.00%
      5-Year Dividend Growth: 2,725.00%

    --- perShareInfo ---
      Most Recent Earnings: 0.29 on 05/26/26
      Next Earnings Date: 08/25/26
      Earnings Per Share ttm: 2.27
      EPS Growth vs. Prev Year: -69.79%
      Annual Dividend & Yield (Paid): 2.16 (4.28%)
      Annual Dividend & Yield (Fwd): 4.86 (9.50%)
      Most Recent Dividend: 0.405 on 05/11/26
      Next Ex-Dividends Date: 05/11/26
      Dividend Payable Date: 05/29/26
      Dividend Payout Ratio: 51.43%

    --- ratios ---
      Price/Earnings ttm: 0.00
      Price/Earnings forward: 13.85
      Price/Earnings to Growth: 0.36
      Return-on-Equity %: 0.00%
      Return-on-Assets %: 0.00%
      Profit Margin %: 1.61%
      Debt/Equity: 0.00
      Price/Sales: 0.78
      Price/Cash Flow: 19.86
      Price/Book: 1.37
      Book Value/Share: 37.43
      Interest Coverage: -1.21
      60-Month Beta: 1.32

    --- dividendHistory ---
      Date: Value
      05/11/26: $0.4050
      05/04/26: $0.1640
      03/30/26: $0.1600
      ... (12+ entries)

Lo que trae cada flag (resumen)

`py fetch_barchart.py TICKER` — Siempre: 27 campos de quote + fundamentals

#	Campo	Descripción	Ejemplo AAPL	Nota
1	ticker	Input del usuario	AAPL
2	symbol	Símbolo en Barchart	AAPL
3	name	Nombre de la empresa	Apple Inc
4	lastPrice	Último precio	310.26	Delayed 15-20 min
5	netChange	Cambio neto en $	-4.94
6	percentChange	Cambio porcentual	-1.57%
7	bid	Bid price actual	313.88
8	ask	Ask price actual	313.97
9	exchange	Exchange donde cotiza	NASDAQ
10	tradeTime	Hora de última operación	06/03/26
11	marketCap	Market cap en $K	4,629,454,720	Dividir /1000 para $
12	sharesOutstanding	Shares en circulación K	14,687,355	En miles
13	annualSales	Ventas anuales	416,161 M	M = millones
14	annualIncome	Ingreso neto anual	112,010 M
15	ebit	EBIT	147,366 M
16	ebitda	EBITDA	159,064 M
17	beta	Beta 60 meses	1.09
18	priceSales	Price/Sales ratio	10.81
19	priceCashFlow	Price/Cash Flow ratio	36.59
20	priceBook	Price/Book ratio	42.25
21	peRatio	Price/Earnings ttm	37.04
22	eps	Earnings Per Share ttm	8.27
23	mostRecentEarnings	Último earnings reportado	$2.01 on 04/30/26
24	nextEarningsDate	Próximo earnings date	07/30/26
25	dividend	Dividendo anual + yield	1.08 (0.35%)
26	mostRecentDividend	Último dividendo pagado	0.270 on 05/11/26
27	sector	Sector de la empresa	Technology

`--insider` agrega: 4 campos

#	Campo	Descripción	Ejemplo AAPL
28	summaryLast3M.buys	Cantidad de transacciones de compra por insiders (3 meses)	0
29	summaryLast3M.buyShares	Acciones compradas por insiders	0
30	summaryLast3M.sells	Cantidad de transacciones de venta	6
31	summaryLast3M.sellShares	Acciones vendidas por insiders	397,759

`--analysts` agrega: 4 períodos × 3 campos = 12 campos

Período	Campos	Ejemplo AAPL
current	rating (texto), value (1-5), analysts (#)	Moderate Buy, 4.12, 42
1_mth_ago	rating, value, analysts	Moderate Buy, 4.12, 42
2_mths_ago	rating, value, analysts	Moderate Buy, 4.07, 42
3_mths_ago	rating, value, analysts	Moderate Buy, 4.07, 42

`--estimates` agrega: 5+ filas × 4 períodos

Fila	Descripción	Ejemplo GGAL Current Qtr
Average Earnings Estimate	EPS estimado promedio	$0.82
Number of Estimates	Cantidad de analistas que estiman	3
High Estimate	EPS estimado más optimista	$1.02
Low Estimate	EPS estimado más pesimista	$0.69
Prior Year	EPS del año anterior en mismo período	$0.94
Growth Rate Est.	Crecimiento estimado vs año anterior	-12.77%

Show full SKILL.md (507 more words)Show less

Lo que NO trae el script

Toda esta data se renderiza con AngularJS y no está disponible en el HTML estático. Hay que usar un headless browser (Playwright, Selenium, etc.).

Página	Datos no disponibles
`/stocks/quotes/{TICKER}/financial-summary`	Solo income/balance/cash flow están disponibles con `--financials`. Growth rates (%) no están
`/stocks/quotes/{TICKER}/options`	Options chain
`/stocks/quotes/{TICKER}/technical-analysis`	RSI, Stochastic, ATR, ADX, Moving Averages, Volatility
`/stocks/quotes/{TICKER}/analyst-ratings`	Price targets (High/Mean/Low), Ratings breakdown (cantidad por categoría)
`/stocks/quotes/{TICKER}/insider-trades`	Transacciones detalladas (solo summary disponible)
`/stocks/quotes/{TICKER}/related-etfs`	Tabla de ETFs relacionados (symbol, name, weight) — todo AngularJS
`/stocks/signals/top-bottom/top`	Screener / Top lists

Cómo funciona — endpoints

Quote + fundamentals

GET https://www.barchart.com/stocks/quotes/{TICKER}

Extrae JSON del atributo data-ng-init='init({...})' (symbol, lastPrice, bid/ask, exchange, tradeTime)
Extrae pares <span class="left">Label</span> + <span class="right">Value</span> para fundamentals

Insider

GET https://www.barchart.com/stocks/quotes/{TICKER}/insider-trades

Extrae resumen de texto plano: "Last 3 Months: X Buys, Y Shares; Z Sells, W Shares"

Analyst ratings

GET https://www.barchart.com/stocks/quotes/{TICKER}/analyst-ratings

Extrae de texto plano el patrón: {Período}\n{Rating}\n{Valor}\nBased on\n{Cantidad}

Earnings estimates

GET https://www.barchart.com/stocks/quotes/{TICKER}/earnings-estimates

Extrae tabla HTML de estimaciones de EPS

Financial summary

GET https://www.barchart.com/stocks/quotes/{TICKER}/financial-summary/{annual|quarterly}

Extrae JSON del atributo data-content con Income Statement (Sales, Net Income), Balance Sheet (Assets, Liabilities) y Cash Flow (Operating Cash Flow, Net Cash Flow) para 5 períodos

Income statement detail

GET https://www.barchart.com/stocks/quotes/{TICKER}/income-statement/{quarterly|annual}

Extrae tabla HTML con Income Statement detallado: Interest Income/Expense, Sales, Net Income, EPS (Basic/Diluted), EBITDA y más (~17 filas)

Balance sheet detail

GET https://www.barchart.com/stocks/quotes/{TICKER}/balance-sheet/{quarterly|annual}

Extrae tabla HTML con Balance Sheet detallado: Cash, Securities, Loans, Total Assets/Liabilities, Shareholders' Equity y más (~23 filas)

Cash flow detail

GET https://www.barchart.com/stocks/quotes/{TICKER}/cash-flow/{quarterly|annual}

Extrae tabla HTML con Cash Flow detallado: Operating, Investing, Financing Cash Flow, Free Cash Flow, Net Cash Flow, End Cash Position y más (~27 filas)

Company profile

GET https://www.barchart.com/stocks/quotes/{TICKER}/profile

Extrae company info desde la sección Company Info (address, website, employees, phone, fax, sector, industries, description)
Extrae 6 tablas de key statistics: overview (enterprise value, float, short interest), financials (last quarter data), growth (returns, CAGR), per-share info (EPS growth, payout ratio, ex-div date), ratios (P/E forward, PEG, ROE, ROA, profit margin, book value/share), dividend history

Flags del script

Flag	Descripción	Endpoint
`TICKER`	Ticker(s) separados por coma (ej: `AAPL,MSFT,GGAL`)	Siempre
`--insider`	Resumen de insider trading últimos 3 meses	`/insider-trades`
`--analysts`	Analyst ratings actual + histórico 3 meses	`/analyst-ratings`
`--estimates`	Earnings estimates (4 períodos)	`/earnings-estimates`
`--financials`	Financial summary anual (default)	`/financial-summary/annual`
`--financials quarterly`	Financial summary trimestral	`/financial-summary/quarterly`
`--income`	Income statement detallado trimestral (default)	`/income-statement/quarterly`
`--income annual`	Income statement detallado anual	`/income-statement/annual`
`--balance`	Balance sheet detallado trimestral (default)	`/balance-sheet/quarterly`
`--balance annual`	Balance sheet detallado anual	`/balance-sheet/annual`
`--cashflow`	Cash flow detallado trimestral (default)	`/cash-flow/quarterly`
`--cashflow annual`	Cash flow detallado anual	`/cash-flow/annual`
`--profile`	Company profile + key statistics	`/profile`
`--output` / `-o`	Guarda output en archivo JSON	-
`--quiet` / `-q`	Output solo JSON a stdout (modo pipe)	-

Se pueden combinar: py fetch_barchart.py AAPL --insider --analysts --estimates --financials --income --balance --cashflow -o aapl_full.json

Notas técnicas

marketCap está en $K (miles). AAPL = 4,629,454,720 → $4.6T
sharesOutstanding está en K (miles)
annualSales/Income usan sufijos: M = millions, K = thousands
Los datos son delayed 15-20 min vs mercado en vivo
Cubre ADRs globales (GGAL, SUPV, BABA, etc.) listados en NYSE/NASDAQ
User-Agent de navegador requerido (ya incluido en el script)
Rate limit: ~300ms entre requests (configurable en el script)

Estructura del skill

skills/barchart/
├── SKILL.md                       # Este archivo — documentación principal
├── references/
│   └── REFERENCE.md               # Referencia técnica detallada
├── scripts/
│   └── fetch_barchart.py          # Script principal (sin dependencias extra)
└── assets/

📖 Referencia técnica: references/REFERENCE.md — tabla campo por campo, detalle de extracción, notas técnicas

Files

SKILL.md and 3 other files (scripts, references) in skills/barchart of gauss314/skills.

SKILL.md
references/API.md
references/REFERENCE.md
scripts/fetch_barchart.py

Open the folder on GitHubat commit 5156f81

Compare with similar skills

Barchart next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Barchart compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Barchart this skillgauss314/skills	248	—	~5.4k	Automated safety check: Pass	MIT	3 mo ago
Financial Researchfirecrawl/web-agent	1.2k	—	~1.1k	Automated safety check: Pass	MIT	5 mo ago
Interlinked Spec AuditQuentinCody/interlinked-cli	178	—	~3.3k	Automated safety check: Pass	MIT	today
Longbridge Market Datasickn33/agentic-awesome-skills	47k	1 repos	~1.7k	Automated safety check: Pass	MIT	yesterday
Longbridge Earningshelsome/folio	271	1 repos	~2.5k	Automated safety check: Pass	None	6 days ago
Equity ResearchrollingSirius/equity-research-skill	453	—	~1.5k	Automated safety check: Pass	MIT	1 mo ago

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Questions about Barchart

What does Barchart do?

Quotes, fundamentals, insider, analyst ratings, earnings estimates, financial summary, income/balance/cashflow detail y company profile (delayed 15-20min). Barchart is an agent skill from gauss314/skills. Quotes, fundamentals, insider, analyst ratings, earnings estimates, financial summary, income/balance/cashflow detail y company profile (delayed 15-20min).

When should I use Barchart?

Barchart fits situations like: tasks that involve Architecture decision records; tasks that involve Financial analysis; tasks that involve Web scraping.

How do I install Barchart in Claude Code?

Run `npx skills add gauss314/skills --skill barchart -a claude-code`. Or copy the skill folder (skills/barchart in gauss314/skills) into .claude/skills/barchart in your project. Claude Code loads it when a task matches its description.

How do I install Barchart in Codex?

Run `npx skills add gauss314/skills --skill barchart -a codex`. Or copy the skill folder (skills/barchart in gauss314/skills) into .agents/skills/barchart in your project. Codex loads it when a task matches its description.

Can I use Barchart in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add gauss314/skills --skill barchart -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/barchart, .gemini/skills/barchart, .github/skills/barchart and .opencode/skills/barchart in your project.

What does Barchart need to run?

Going by SKILL.md and its folder, Barchart needs Python for the scripts in its folder and the command-line tools its instructions call (pip). Our summary lists: Python 3.

Does Barchart access the network?

SKILL.md names 2 domains. In commands or code: barchart.com and gfgsa.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Barchart safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Barchart use?

Barchart is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Barchart use?

About 5.4k tokens (SKILL.md is roughly 22k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 7.8k tokens, read only when the agent opens those files.

What are the alternatives to Barchart?

Skills that share tags, products or a category with Barchart: Financial Research (firecrawl/web-agent, 1.2k stars), Interlinked Spec Audit (QuentinCody/interlinked-cli, 178 stars), Longbridge Market Data (sickn33/agentic-awesome-skills, 47k stars) and Longbridge Earnings (helsome/folio, 271 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Barchart?

gauss314 (a GitHub user) maintains it in gauss314/skills, which has 248 GitHub stars. The repository holds 32 skills in this directory. The repository was last updated on June 14, 2026.

Source: gauss314/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Barchart

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Barchart Scraper

⚠️ Datos clave

Instalación

Scripts

Uso rápido

Output real por flag

py fetch_barchart.py AAPL (quote + fundamentals)

py fetch_barchart.py GGAL (mismos campos para ADR)

--insider (agrega)

--analysts (agrega)

--estimates (agrega)

--financials annual (agrega)

--financials quarterly (agrega)

--income quarterly (agrega income statement detallado)

--balance quarterly (agrega balance sheet detallado)

--cashflow quarterly (agrega cash flow detallado)

--profile (agrega company profile + key statistics)

Lo que trae cada flag (resumen)

py fetch_barchart.py TICKER — Siempre: 27 campos de quote + fundamentals

--insider agrega: 4 campos

--analysts agrega: 4 períodos × 3 campos = 12 campos

--estimates agrega: 5+ filas × 4 períodos

Lo que NO trae el script

Cómo funciona — endpoints

Quote + fundamentals

Insider

Analyst ratings

Earnings estimates

Financial summary

Income statement detail

Balance sheet detail

Cash flow detail

Company profile

Flags del script

Notas técnicas

Estructura del skill

Files

Compare with similar skills

Similar skills

More from gauss314/skills

Related

Questions about Barchart

`py fetch_barchart.py AAPL` (quote + fundamentals)

`py fetch_barchart.py GGAL` (mismos campos para ADR)

`--insider` (agrega)

`--analysts` (agrega)

`--estimates` (agrega)

`--financials` annual (agrega)

`--financials quarterly` (agrega)

`--income quarterly` (agrega income statement detallado)

`--balance quarterly` (agrega balance sheet detallado)

`--cashflow quarterly` (agrega cash flow detallado)

`--profile` (agrega company profile + key statistics)

`py fetch_barchart.py TICKER` — Siempre: 27 campos de quote + fundamentals

`--insider` agrega: 4 campos

`--analysts` agrega: 4 períodos × 3 campos = 12 campos

`--estimates` agrega: 5+ filas × 4 períodos