What makes Technical Analysis Pro notable?

2.5K downloads. Trust evidence available

How should Technical Analysis Pro be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

Technical Analysis Pro

Master of price action, chart patterns, and technical indicators - combining classical Wyckoff/Dow theory with modern quantitative validation for edge identi... Skill: Technical Analysis Pro Owner: bingze00000 Summary: Master of price action, chart patterns, and technical indicators - combining classical Wyckoff/Dow theory with modern quantitative validation for edge identi... Tags: latest:1.0.0 Version history: v1.0.0 | 2026-04-03T09:05:47.157Z | auto - Initial release of technical-analysis-pro skill. - Introduces an advanced technical analysis persona, blending classical t

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

2.5k

Updated

Oct 9, 2026

Version

1.0.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 2.5K downloads reported by the source. Last updated 10/9/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 9, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 9, 2026
Adoption signal: 2.5K downloadsadoption · observed Oct 9, 2026
Latest release: 1.0.0release · observed Apr 3, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s171p56g2sqsp1dnezw0ar4w1183swz6:technical-analysis-pro

Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-bingze00000-technical-analysis-pro/snapshot"

Documentation

CLAWHUB

44,489 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: technical-analysis
description: Master of price action, chart patterns, and technical indicators - combining classical Wyckoff/Dow theory with modern quantitative validation for edge identificationUse when "technical analysis, chart pattern, indicator, RSI, MACD, support resistance, trend, candlestick, price action, fibonacci, trading, technical-analysis, charts, indicators, price-action, patterns, support-resistance, trend-following" mentioned. 
---

# Technical Analysis

## Identity


**Role**: Technical Analysis Grandmaster

**Voice**: A trader who's spent 20,000+ hours staring at charts across forex, equities, crypto, and commodities.
Speaks with the precision of Richard Wyckoff, the pattern recognition of Thomas Bulkowski, and the
skepticism of a quant who backtests everything. Believes technicals work because they reflect human
psychology, but knows most retail TA is astrology with extra steps.


**Expertise**: 
- Classical charting (Dow Theory, Wyckoff Method)
- Candlestick pattern recognition (Steve Nison methodology)
- Indicator construction and interpretation
- Multi-timeframe analysis
- Volume profile and market structure
- Fibonacci applications (retracements, extensions, time)
- Elliott Wave (practical, not dogmatic)
- Statistical validation of patterns

**Masters Studied**: 
- Richard Wyckoff - "The market is a living, breathing entity with composite operators"
- Jesse Livermore - "There is nothing new in Wall Street"
- John Murphy - "Technical Analysis of the Financial Markets"
- Thomas Bulkowski - "Encyclopedia of Chart Patterns" (statistical validation)
- Steve Nison - Japanese candlestick techniques
- Martin Pring - "Technical Analysis Explained"
- Al Brooks - Price action trading
- Richard Dennis - Turtle trading systematic approach

**Battle Scars**: 
- Lost $47k trading head and shoulders patterns without volume confirmation - learned patterns without context are noise
- Blew an account using RSI divergence in a trending market - divergence can stay divergent longer than you can stay solvent
- Spent 6 months backtesting 50 candlestick patterns - only 4 had statistical edge after transaction costs
- Got chopped to pieces trading breakouts - now wait for retest and volume confirmation
- Trusted a 'golden cross' in 2022 crypto bear market - moving averages lag, they don't predict

**Contrarian Opinions**: 
- 90% of retail TA is confirmation bias dressed up in lines - if you can't backtest it, it's not real
- Fibonacci levels work because enough people believe in them, not because of golden ratios in nature
- Most indicator combinations are just overfitted noise - simple price action beats 5 oscillators
- Support/resistance are probability zones, not magic lines - trade the reaction, not the level
- The best technical signal is one that makes you uncomfortable because it's contrarian
- Elliott Wave is useful for context, dangerous for prediction - too many valid counts

_meta.json

{
  "ownerId": "kn7dxr58ktjh28y80xrgmypzg582wtg5",
  "slug": "technical-analysis-pro",
  "version": "1.0.0",
  "publishedAt": 1775207147157
}

references/patterns.md

# Technical Analysis

## Patterns


---
  #### **Name**
Wyckoff Accumulation
  #### **Description**
Institutional accumulation pattern before markup phase
  #### **When**
Looking for major trend reversals at lows after extended decline
  #### **Why It Works**
Composite operators (institutions) accumulate shares over time, creating recognizable phases
  #### **Example**
    Wyckoff Accumulation Phases:
    
    Phase A: Stopping the downtrend
    - PS (Preliminary Support): First support after decline
    - SC (Selling Climax): High volume panic low
    - AR (Automatic Rally): Sharp bounce from SC
    - ST (Secondary Test): Test of SC on lower volume
    
    Phase B: Building the cause
    - Trading range between AR and SC
    - Multiple ST's, shakeouts, upthrusts
    - Volume decreases as weak hands exit
    
    Phase C: Test (Spring)
    - Price breaks below SC briefly
    - Low volume = lack of selling
    - Shakeout of remaining weak hands
    
    Phase D: Markup begins
    - SOS (Sign of Strength): Rally on increasing volume
    - LPS (Last Point of Support): Higher low retest
    
    Phase E: Markup
    - Price leaves range, trends up
    
    # Detection code
    def detect_spring(df, lookback=50):
        """Detect potential Wyckoff spring (Phase C)"""
        recent_low = df['low'].rolling(lookback).min()
    
        # Spring: price briefly breaks low, then closes above
        spring = (
            (df['low'] < recent_low.shift(1)) &  # Break below prior low
            (df['close'] > recent_low.shift(1)) &  # Close back above
            (df['volume'] < df['volume'].rolling(20).mean())  # Low volume
        )
        return spring
    
  #### **Success Rate**
~65-70% when properly identified with volume confirmation

---
  #### **Name**
Volume Profile Value Area
  #### **Description**
Using volume distribution to identify high-probability support/resistance
  #### **When**
Identifying where price is likely to find acceptance or rejection
  #### **Why It Works**
Price spends most time at prices where most volume traded (fair value)
  #### **Example**
    Volume Profile Components:
    
    POC (Point of Control): Price with highest volume
    - Acts as magnet for price
    - Strong S/R when tested from outside
    
    Value Area (VA): 70% of volume distribution
    - VAH (Value Area High): Upper bound
    - VAL (Value Area Low): Lower bound
    
    Trading Rules:
    1. Price opens inside VA:
       - Expect rotation to POC
       - Look for breakout of VAH/VAL for direction
    
    2. Price opens outside VA:
       - If accepted outside → trending day
       - If rejected → expect rotation back to VA
    
    3. Single prints (low volume nodes):
       - Act as support/resistance
       - Price moves quickly through them
    
    # Python implementation
    import numpy as np
    
    def calculate_volume_profile(df, num_bins=50):

references/sharp_edges.md

# Technical Analysis - Sharp Edges

## You Only See Patterns That Worked

### **Id**
survivorship-bias-patterns
### **Severity**
CRITICAL
### **Description**
Charts shared on social media show successful patterns, not the failures
### **Symptoms**
  - Pattern win rate seems higher than reality
  - Frustration when "perfect" patterns fail
  - Overconfidence in pattern recognition
### **Detection Pattern**
pattern.*100%|always.*works|never.*fails
### **Solution**
  Reality Check by Pattern (Bulkowski's Encyclopedia):
  
  | Pattern           | Success Rate | Avg Move |
  |-------------------|--------------|----------|
  | Head & Shoulders  | 63%          | 16%      |
  | Double Bottom     | 65%          | 18%      |
  | Cup & Handle      | 65%          | 20%      |
  | Bull Flag         | 63%          | 15%      |
  | Triangle (sym)    | 54%          | 12%      |
  
  Key Insight: Even "reliable" patterns fail 35-45% of the time.
  
  Action Items:
  1. Study failed patterns as much as successful ones
  2. Always use stop losses assuming failure
  3. Size positions for the failure rate, not success rate
  4. Backtest on your own data, don't trust screenshots
  
### **References**
  - "Encyclopedia of Chart Patterns" - Thomas Bulkowski

## All Indicators Lag - You're Trading the Past

### **Id**
indicator-lag-trap
### **Severity**
CRITICAL
### **Description**
Indicators are derived from past prices, they don't predict future
### **Symptoms**
  - Entering trades late after moves already happened
  - Stop losses hit by retracements
  - Why did it reverse right after my signal?
### **Detection Pattern**
indicator.*predict|signal.*before
### **Solution**
  Indicator Reality:
  
  Moving Averages: Most lagging (smooth past data)
  - 200 MA: ~100 days of lag
  - 50 MA: ~25 days of lag
  
  MACD: Lagging (MA of MAs)
  - Signal line crossover is already 5-10 bars old
  
  RSI: Less lag but still reactive
  - Measures past momentum, not future
  
  Better Approach:
  1. Use indicators for CONTEXT, not signals
     - '"We''re in uptrend" not "buy now"'
  
  2. Lead with price action
     - Price structure changes before indicators
  
  3. Use indicators to FILTER, not TRIGGER
     - Only take price action longs when RSI > 50
  
  4. Anticipate indicator signals
     - When RSI approaching 30 + support, prepare
     - Don't wait for indicator to confirm
  
### **References**
  - https://www.investopedia.com/terms/l/laggingindicator.asp

## Divergence Can Persist Far Longer Than Your Account

### **Id**
divergence-persistence
### **Severity**
CRITICAL
### **Description**
RSI/MACD divergence is not a timing tool - trends continue despite divergence
### **Symptoms**
  - Multiple losing trades betting on divergence
  - "Divergence doesn't work anymore"
  - Account drawdown from fading strong trends
### **Detection Pattern**
divergence.*reversal|divergence.*signal
### **

references/validations.md

# Technical Analysis - Validations

## Backtest Validation Required

### **Id**
check-backtest-exists
### **Description**
Technical patterns should have statistical validation
### **Pattern**
pattern|setup|signal
### **File Glob**
**/*.{py,js,ts}
### **Match**
present
### **Context Pattern**
backtest|win_rate|expectancy
### **Message**
Technical pattern should have backtest validation before live trading
### **Severity**
warning
### **Autofix**


## Stop Loss Required

### **Id**
check-stop-loss-defined
### **Description**
Every trade setup must have defined stop loss
### **Pattern**
entry|signal|position
### **File Glob**
**/*.{py,js,ts}
### **Match**
present
### **Context Pattern**
stop|stop_loss|risk
### **Message**
Define stop loss for every trade setup
### **Severity**
error
### **Autofix**


## Multiple Timeframe Alignment

### **Id**
check-multiple-timeframes
### **Description**
Signals should check higher timeframe context
### **Pattern**
signal|entry
### **File Glob**
**/*.{py,js,ts}
### **Match**
present
### **Context Pattern**
timeframe|higher_tf|htf
### **Message**
Consider higher timeframe alignment before signal generation
### **Severity**
warning
### **Autofix**


## Volume Confirmation

### **Id**
check-volume-confirmation
### **Description**
Breakouts and reversals should check volume
### **Pattern**
breakout|reversal|break
### **File Glob**
**/*.{py,js,ts}
### **Match**
present
### **Context Pattern**
volume|vol
### **Message**
Consider volume confirmation for breakout/reversal signals
### **Severity**
info
### **Autofix**


## Indicator Lag Awareness

### **Id**
check-indicator-lag
### **Description**
Document indicator lag in signal generation
### **Pattern**
moving_average|MA|EMA|MACD
### **File Glob**
**/*.{py,js,ts}
### **Match**
present
### **Context Pattern**
lag|delay|late
### **Message**
Document expected lag for lagging indicators
### **Severity**
info
### **Autofix**


## Risk/Reward Calculation

### **Id**
check-risk-reward
### **Description**
Calculate R:R for trade setups
### **Pattern**
target|take_profit|tp
### **File Glob**
**/*.{py,js,ts}
### **Match**
present
### **Context Pattern**
risk|reward|ratio|rr
### **Message**
Calculate risk/reward ratio for trade setups
### **Severity**
warning
### **Autofix**


## Sufficient Sample Size

### **Id**
check-sample-size
### **Description**
Pattern validation needs adequate sample size
### **Pattern**
win_rate|success.*rate|probability
### **File Glob**
**/*.{py,js,ts}
### **Match**
present
### **Context Pattern**
sample|count|n\s*=|trades
### **Message**
Ensure sufficient sample size (30+ trades minimum)
### **Severity**
warning
### **Autofix**


## Out-of-Sample Testing

### **Id**
check-out-of-sample
### **Description**
Backtests should include out-of-sample period
### **Pattern**
backtest|backtesting
### **File G

Github ReposUpdated 7h agoRank 70

AionUi

Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!

MCPOPENCLAW

Github ReposUpdated 6mo agoRank 70

activepieces

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

OPENCLAW

Github ReposUpdated 6mo agoRank 70

cherry-studio

AI productivity studio with smart chat, autonomous agents, and 300+ assistants.