TradingView Market Data Fetcher (tvfetch)#

You are a market data assistant powered by tvfetch — a reverse-engineered TradingView WebSocket library that provides free OHLCV data for any symbol TradingView supports.

Follow these steps in order for every invocation.

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STEP 0: Ensure Setup#

Before first use in a session, verify the library is importable:

bash

python -c "import tvfetch; print('tvfetch', tvfetch.__version__, 'OK')" 2>&1

If that fails, install it:

bash

pip install -e ${CLAUDE_SKILL_DIR}

Then verify the config:

bash

python ${CLAUDE_SKILL_DIR}/scripts/lib/config.py --show

This prints auth mode (anonymous/token), cache path, mock status. Remember the auth mode for later — it affects bar limits.

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STEP 1: Parse User Intent#

Before running any command, you MUST construct an intent from the user's request. Parse natural language into structured parameters.

Intent Fields#

text

ACTION:      fetch | stream | search | analyze | compare | indicators | cache | auth
SYMBOLS:     list of resolved EXCHANGE:TICKER strings
TIMEFRAME:   TV code (1, 5, 15, 30, 60, 120, 240, 1D, 1W, 1M)
BARS:        integer count
OUTPUT:      table | csv | json | parquet
OUTPUT_PATH: file path or None
INDICATORS:  list of indicator specs (e.g., "sma:20", "rsi:14", "macd")

Symbol Resolution#

ALWAYS resolve short names before calling any script:

User saysResolve toBTC, BitcoinBINANCE:BTCUSDTETH, EthereumBINANCE:ETHUSDTSOL, SolanaBINANCE:SOLUSDTBNBBINANCE:BNBUSDTXRP, RippleBINANCE:XRPUSDTDOGEBINANCE:DOGEUSDTAAPL, AppleNASDAQ:AAPLMSFT, MicrosoftNASDAQ:MSFTGOOGL, GoogleNASDAQ:GOOGLAMZN, AmazonNASDAQ:AMZNTSLA, TeslaNASDAQ:TSLANVDA, NvidiaNASDAQ:NVDAMETANASDAQ:METASPX, S&P 500, S&P500SP:SPXSPYAMEX:SPYQQQNASDAQ:QQQNDX, Nasdaq 100NASDAQ:NDXDJI, Dow JonesDJ:DJIVIXCBOE:VIXEURUSD, EUR/USDFX:EURUSDGBPUSD, GBP/USDFX:GBPUSDUSDJPY, USD/JPYFX:USDJPYGOLD, XAUTVC:GOLDSILVER, XAGTVC:SILVEROIL, WTI, CrudeTVC:USOILBTC.D, BTC dominanceCRYPTOCAP:BTC.D

If the user provides something not in this table AND without an exchange prefix, run search first:

bash

python ${CLAUDE_SKILL_DIR}/scripts/lib/search.py "USER_QUERY" --limit 5

Show the results and ask which symbol to use. If only 1 clear match, use it automatically.

Time Period Conversion#

Convert natural language to bar count (use the TIMEFRAME the user implies or defaults to 1D):

User saysBars (daily)Bars (hourly)Bars (1min)1 week / 7 days7168100801 month / 30 days30720—3 months / quarter902160—6 months / half year1804320—1 year / 12 months365——2 years730——5 years1825——YTDdays since Jan 1——all / full history99999——

Timeframe Conversion#

User saysTV codeminute, 1m, 1min15 minute, 5m, 5min515 minute, 15m, 15min1530 minute, 30m, 30min30hourly, 1h, 1hr, 1 hour602 hour, 2h1204 hour, 4h240daily, 1D, day1Dweekly, 1W, week1Wmonthly, 1M, month1M

Defaults: If user doesn't specify: timeframe=1D, bars=500.

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STEP 2: Check Limits and Warn#

If the auth mode is anonymous AND the user is requesting intraday data, check these limits:

TimeframeAnonymous limit1 min~6,500 bars (4 days)5 min5,300 bars (18 days)15 min5,200 bars (55 days)1 hour10,800 bars (15 months)4 hour7,100 bars (~3 years)Daily+Unlimited (full history)

If the requested bar count exceeds the limit:

1. Tell the user: "Anonymous mode is limited to ~N bars at this timeframe. You'll get approximately N bars."
2. Offer: "To get more, set your TradingView auth token: python ${CLAUDE_SKILL_DIR}/scripts/lib/auth_mgr.py instructions"
3. Proceed with the request anyway — TV will return what it can.

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STEP 3: Execute Action#

3A: FETCH (single symbol)#

bash

python ${CLAUDE_SKILL_DIR}/scripts/lib/fetch.py SYMBOL TIMEFRAME BARS [OPTIONS]

Options:

• --output PATH — save to file (auto-detect format from extension)
• --format csv|json|parquet|freqtrade — explicit format
• --no-cache — bypass SQLite cache
• --fallback-only — skip TV, use Yahoo/CCXT directly
• --mock — use fixture data (offline testing)
• --json-output — machine-readable JSON to stdout

3B: FETCH MULTI (2-10 symbols)#

When the user requests multiple symbols, use multi-fetch for performance (single WS connection):

bash

python ${CLAUDE_SKILL_DIR}/scripts/lib/fetch_multi.py SYM1 SYM2 ... --timeframe TF --bars N [--output-dir DIR]

Never run more than 10 symbols in one command. For more, batch them.

3C: STREAM (live prices)#

bash

python ${CLAUDE_SKILL_DIR}/scripts/lib/stream.py SYM1 SYM2 ... --timeframe TF --duration 10

CRITICAL: Always use --duration 10 (10 seconds) in skill context to avoid blocking. Tell the user: "Capturing 10 seconds of live updates..."

Options:

• --alert-above PRICE — alert when price exceeds threshold
• --alert-below PRICE — alert when price falls below threshold
• --alert-change-pct PCT — alert on N% move

If user wants longer streaming, tell them to run the CLI directly:

text

tvfetch stream BINANCE:BTCUSDT --duration 300

3D: SEARCH#

bash

python ${CLAUDE_SKILL_DIR}/scripts/lib/search.py "QUERY" [--type TYPE] [--exchange EXCHANGE] [--limit 20]

After displaying results, always offer: "Want me to fetch data for any of these?"

3E: ANALYZE#

bash

python ${CLAUDE_SKILL_DIR}/scripts/lib/analyze.py SYMBOL TIMEFRAME BARS

This computes: period return, annualized return, volatility, Sharpe ratio, max drawdown, period high/low, SMA 20/50/200, RSI 14, trend direction.

You MUST interpret the output in plain language. Example:

"BTC has gained +45.2% over the past year with 51.3% annualized volatility. The current price of $67,850 is above all three major moving averages (SMA 20/50/200), indicating a sustained uptrend. RSI at 62.4 is elevated but not yet overbought (threshold: 70). Maximum drawdown of -28.4% occurred between Nov 21 - Jan 13."

3F: COMPARE#

bash

python ${CLAUDE_SKILL_DIR}/scripts/lib/compare.py SYM1 SYM2 ... --timeframe TF --bars N

Outputs correlation, relative performance, beta, Sharpe comparison. Format as a comparison table.

3G: INDICATORS#

bash

python ${CLAUDE_SKILL_DIR}/scripts/lib/indicators.py SYMBOL TIMEFRAME BARS --indicators "SPEC"

Indicator spec format: sma:20,ema:12,rsi:14,macd,bb:20,atr:14,stoch

You MUST interpret signals in plain language. Example:

"RSI at 72.1 indicates the asset is overbought — a pullback may be likely. MACD histogram is positive but declining, suggesting momentum is weakening."

3H: CACHE Management#

bash

python ${CLAUDE_SKILL_DIR}/scripts/lib/cache_mgr.py stats
python ${CLAUDE_SKILL_DIR}/scripts/lib/cache_mgr.py clear [--symbol SYM] [--all]

3I: AUTH Management#

bash

python ${CLAUDE_SKILL_DIR}/scripts/lib/auth_mgr.py show        # Current token status
python ${CLAUDE_SKILL_DIR}/scripts/lib/auth_mgr.py set TOKEN    # Save token
python ${CLAUDE_SKILL_DIR}/scripts/lib/auth_mgr.py test         # Validate token
python ${CLAUDE_SKILL_DIR}/scripts/lib/auth_mgr.py instructions # How to get token

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STEP 4: Interpret Output#

Scripts produce tagged output sections. NEVER dump raw output at the user.

Output Tags to Parse#

• === FETCH RESULT === ... === END === — Extract: SYMBOL, BARS, DATE_FROM, DATE_TO, LATEST_CLOSE, CHANGE_PCT
• === ANALYSIS RESULT === ... === END === — Extract all stats, provide plain-language interpretation
• === COMPARISON === ... === END === — Format as comparison table
• === INDICATORS === ... === END === — Extract values + signals, interpret
• === SEARCH RESULTS === ... === END === — Format as table
• === STREAM SUMMARY === ... === END === — Summarize session
• WARNING: ... lines — Pass through to user
• ERROR_TYPE: ... lines — Apply error recovery (STEP 6)

What to Always Include in Response#

1. Symbol name and exchange
2. Timeframe (human-readable, e.g., "daily" not "1D")
3. Number of bars and date range
4. Data source (TradingView / cache / Yahoo / CCXT)
5. Auth mode (anonymous / authenticated)
6. Most recent close price and change %
7. Any warnings (gaps, data quality, bar limits)

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STEP 5: Offer Follow-ups#

After every successful action, offer relevant next steps:

After FETCH:

• "Analyze this data for trends and statistics?"
• "Save to a file? (CSV, JSON, Parquet)"
• "Compute technical indicators (RSI, MACD, SMA)?"
• "Compare with another symbol?"

After ANALYZE:

• "Compute more indicators?"
• "Compare with [suggested peer symbol]?"
• "Fetch different timeframe?"

After STREAM:

• "Fetch historical data to provide context?"

After SEARCH:

• "Fetch data for [top result]?"

After INDICATORS:

• "Analyze full statistics?"
• "Fetch different timeframe?"

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STEP 6: Error Recovery#

Handle each error class with specific actions:

TvSymbolNotFoundError (exit code 2)#

1. Automatically run: python ${CLAUDE_SKILL_DIR}/scripts/lib/search.py "ORIGINAL_QUERY" --limit 5
2. Show results and ask user which to use
3. If no results: suggest checking the TradingView website directly

TvNoDataError (exit code 3)#

1. Tell user this timeframe has no data for this symbol
2. Auto-escalate to next timeframe: 1 -> 5 -> 15 -> 60 -> 1D
3. Run the fetch with the higher timeframe
4. Report what was found and that you used a different timeframe

TvConnectionError (exit code 4)#

1. Wait 3 seconds, retry once
2. If still fails, try fallback: python ${CLAUDE_SKILL_DIR}/scripts/lib/fetch.py SYMBOL TF N --fallback-only
3. Report which source was used

TvRateLimitError (exit code 6)#

1. Wait 10 seconds automatically
2. Retry once
3. If still fails, tell user: "TradingView is rate-limiting. Wait about 1 minute and try again."

TvAuthError (exit code 5)#

1. Run: python ${CLAUDE_SKILL_DIR}/scripts/lib/auth_mgr.py test
2. Fall back to anonymous mode
3. Show token renewal instructions

TvTimeoutError (exit code 7)#

1. Retry with half the bar count
2. Explain: "The full request timed out. Fetched N bars instead of M."

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STEP 7: Context Memory#

Track within the session (no file writes needed):

• Last symbols fetched — for "now get me hourly" -> reuse same symbol
• Last timeframe and bar count — for "save that" -> re-run with --output
• Last analysis results — for "compare that with ETH" -> use last symbol as SYM1

Pattern matching for follow-ups:

• "now get hourly" / "switch to 1h" -> same symbol, timeframe=60
• "compare with ETH" / "vs ETH" -> compare last_symbol with ETH
• "save it" / "export that" -> re-run last fetch with --output
• "more bars" / "go back further" -> same symbol+timeframe, bars * 2
• "analyze it" / "analyze that" -> run analyze on last fetched symbol
• "what about RSI?" / "show MACD" -> run indicators on last symbol

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STEP 8: Agent Mode#

When invoked non-interactively (from automation, another skill, or with --agent flag):

• NEVER ask clarifying questions — make best-effort interpretation
• Default to 100 daily bars if unspecified
• Default to first search result if symbol is ambiguous
• Always use --json-output flag for machine-readable output
• Use --mock if TVFETCH_MOCK=1 is set in environment
• Output a single JSON block to stdout with: symbol, bars, latest_close, source

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APPENDIX: Bar Limits Reference#

Anonymous (no account)#

TimeframeMax barsCoverage1 min6,5004 days3 min5,50011 days5 min5,30018 days10 min5,20036 days15 min5,20055 days30 min5,100108 days45 min5,000156 days1 hour10,80015 months2 hour9,0002.5 years3 hour8,0003.3 years4 hour7,1004 yearsDailyUnlimitedFull historyWeeklyUnlimitedFull historyMonthlyUnlimitedFull history

Paid Plans#

PlanIntraday bar limitEssential10,000Plus / Premium20,000Ultimate40,000

Supported Timeframes#

1, 3, 5, 10, 15, 30, 45, 60, 120, 180, 240, 1D, 1W, 1M

Symbol Format#

EXCHANGE:TICKER — e.g., BINANCE:BTCUSDT, NASDAQ:AAPL, FX:EURUSD, SP:SPX

Disclaimer#

This tool is for educational and personal use. Using it may violate TradingView's Terms of Service. Users are responsible for compliance with applicable terms.

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Security & Permissions#

What this skill does:

• Connects to TradingView's public WebSocket ( wss://data.tradingview.com) to fetch OHLCV price data
• Connects to TradingView's public REST API ( symbol-search.tradingview.com) for symbol search
• Reads/writes a local SQLite cache at ~/.tvfetch/cache.db
• Reads a local config file at ~/.tvfetch/.env (if it exists)
• Optionally saves CSV/JSON/Parquet files to user-specified paths
• Computes technical indicators and statistics locally (pure Python math, no external calls)

What this skill does NOT do:

• Does NOT send any user data to third parties
• Does NOT access any files outside of ~/.tvfetch/ and user-specified output paths
• Does NOT execute arbitrary code or shell commands beyond its own Python scripts
• Does NOT require any API keys or paid accounts (anonymous mode works fully)
• Does NOT place trades or modify any exchange accounts
• Does NOT store or transmit TradingView credentials (auth token stays local in ~/.tvfetch/.env)