Agent skill

Technical Analyst

by tradermonty in tradermonty/claude-trading-skills

This skill should be used when analyzing weekly price charts for stocks, stock indices, cryptocurrencies, or forex pairs.

MITAuto-check passedBusiness, Finance & HR

Install Technical Analyst

skills CLI
$ npx skills add tradermonty/claude-trading-skills --skill technical-analyst -a claude-code

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

GitHub CLI
$ gh skill install tradermonty/claude-trading-skills technical-analyst --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/tradermonty/claude-trading-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/technical-analyst .claude/skills/technical-analyst && 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/

Facts

Skill name
technical-analyst
GitHub stars
3k
Used in
5 other repos
Token cost
~4.6k tokens
SKILL.md length
1,829 words
Files
10 (incl. scripts, references, assets)
Skills in repo
74
Repo updated
First seen
Licence
MIT

At a glance

This skill should be used when analyzing weekly price charts for stocks, stock indices, cryptocurrencies, or forex pairs.

  • Works in 6 steps: Receive Chart Images → Load Technical Analysis Framework → Analyze Each Chart Systematically → …
  • The user provides chart images and requests technical analysis
  • SKILL.md covers Overview, When to Use, Prerequisites and Output, plus 6 more sections
  • Runs Python scripts from its folder; calls python3

What it does

Technical Analyst is an agent skill from tradermonty/claude-trading-skills. This skill should be used when analyzing weekly price charts for stocks, stock indices, cryptocurrencies, or forex pairs. Use this skill when the user provides chart images and requests technical analysis, trend identification, support/resistance levels, scenario planning, or probability assessments based purely on chart data without consideration of news or fundamental factors.

Its SKILL.md is about 4.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 13 other files, including scripts, reference files and assets (for example `assets/analysis_template.md`, `references/contrarian-confirmation-checklist.md` and `references/technical_analysis_framework.md`).

It sits in Business, Finance & HR, covering Crypto and DeFi analysis. The repository describes itself as: Claude Code skills for equity investors and traders — market analysis, technical charting, economic calendars, screeners, and trading strategy development. The licence is MIT.

When your agent uses it

  • The user provides chart images and requests technical analysis
  • Trend identification
  • Support/resistance levels
  • Scenario planning

Example prompts

  • “/technical-analyst”

Requirements

  • Python 3

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Receive Chart Images
  2. Load Technical Analysis Framework
  3. Analyze Each Chart Systematically
  4. Develop Probabilistic Scenarios
  5. Generate Analysis Report
  6. Repeat for Multiple Charts

What it can do on your machine

Read from SKILL.md and the folder at commit eab8d5c. 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 5 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    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

Technical Analyst loads about 4.6k tokens when it runs, and up to ~11k if it reads all its reference files. Until then it costs about 100 tokens; SKILL.md has 1,829 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~100
When it runs · the whole SKILL.md, loaded when a task matches
~4.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~11k

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 tradermonty/claude-trading-skills at commit eab8d5c, republished under its MIT licence (© tradermonty). 1,829 words, ~4,591 tokens.

Download SKILL.mdSave it as .claude/skills/technical-analyst/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.
name
technical-analyst
description
This skill should be used when analyzing weekly price charts for stocks, stock indices, cryptocurrencies, or forex pairs. Use this skill when the user provides chart images and requests technical analysis, trend identification, support/resistance levels, scenario planning, or probability assessments based purely on chart data without consideration of news or fundamental factors.

Technical Analyst

Overview

This skill enables comprehensive technical analysis of weekly price charts. Analyze chart images to identify trends, support and resistance levels, moving average relationships, volume patterns, and develop probabilistic scenarios for future price movement. All analysis is conducted objectively using only chart data, without influence from news, fundamentals, or market sentiment.

When to Use

  • User provides weekly chart images (stocks, indices, crypto, forex) and requests technical analysis
  • Need to identify trend direction, strength, and potential reversal points
  • Looking for support/resistance levels and key price zones
  • Want probabilistic scenario planning with specific price targets
  • Require objective chart-based analysis without fundamental or news considerations

Prerequisites

  • Chart Images: User must provide weekly timeframe chart images for analysis
  • No API Keys Required: This skill analyzes user-provided images; no external data fetches

Output

This skill generates markdown analysis reports saved to the reports/ directory:

  • File format: [SYMBOL]_technical_analysis_[YYYY-MM-DD].md
  • Content: Comprehensive analysis including trend, S/R levels, MA analysis, volume, patterns, and 2-4 probabilistic scenarios with targets and invalidation levels

Core Principles

  1. Pure Chart Analysis: Base all conclusions exclusively on technical data visible in the chart
  2. Systematic Approach: Follow a structured methodology for each chart analysis
  3. Objective Assessment: Avoid subjective bias; focus on observable patterns and data
  4. Probabilistic Scenarios: Express future possibilities as probability-weighted scenarios
  5. Sequential Processing: Analyze each chart individually and document findings immediately

Analysis Workflow

Step 1: Receive Chart Images

When the user provides one or more weekly chart images for analysis:

  1. Confirm receipt of all chart images
  2. Identify the number of charts to analyze
  3. Note any specific focus areas requested by the user
  4. Proceed to analyze charts sequentially, one at a time
Step 2: Load Technical Analysis Framework

Before beginning analysis, read the comprehensive technical analysis methodology:

Read: references/technical_analysis_framework.md

This reference contains detailed guidance on:

  • Trend analysis and classification
  • Support and resistance identification
  • Moving average interpretation
  • Volume analysis
  • Chart patterns and candlestick analysis
  • Scenario development and probability assignment
  • Analysis discipline and objectivity
Step 3: Analyze Each Chart Systematically

For each chart image, conduct a systematic analysis following this sequence:

3.1 Trend Analysis
  • Identify trend direction (uptrend, downtrend, sideways)
  • Assess trend strength (strong, moderate, weak)
  • Note trend duration and potential exhaustion signals
  • Examine higher highs/lows or lower highs/lows pattern
3.2 Support and Resistance Analysis
  • Mark significant horizontal support levels
  • Mark significant horizontal resistance levels
  • Identify trendline support/resistance
  • Note any support-resistance role reversals
  • Assess confluence zones where multiple S/R levels align
3.3 Moving Average Analysis
  • Determine price position relative to 20-week, 50-week, and 200-week MAs
  • Assess MA alignment (bullish, bearish, or neutral configuration)
  • Note MA slope (rising, falling, flat)
  • Identify any recent or pending MA crossovers
  • Observe MAs acting as dynamic support or resistance
3.4 Volume Analysis
  • Assess overall volume trend (increasing, decreasing, stable)
  • Identify volume spikes and their context (at support/resistance, on breakouts)
  • Check for volume confirmation or divergence with price
  • Note any volume climax or exhaustion patterns
3.5 Chart Patterns and Price Action
  • Identify any reversal patterns (hammers, shooting stars, engulfing patterns, etc.)
  • Identify any continuation patterns (flags, triangles, etc.)
  • Note significant candlestick formations
  • Observe recent breakouts or breakdowns
3.6 Synthesize Observations
  • Integrate all technical elements into coherent current assessment
  • Identify the most significant factors influencing the chart
  • Note any conflicting signals or ambiguity
  • Establish key levels that will determine future direction
Step 4: Develop Probabilistic Scenarios

For each analyzed chart, create 2-4 distinct scenarios for future price movement:

Scenario Structure

Each scenario must include:

  1. Scenario Name: Clear, descriptive title (e.g., "Bull Case: Breakout Above Resistance")
  2. Probability Estimate: Percentage likelihood based on technical factors (must sum to 100% across all scenarios)
  3. Description: What this scenario entails and how it would unfold
  4. Supporting Factors: Technical evidence supporting this scenario (minimum 2-3 factors)
  5. Target Levels: Expected price levels if scenario plays out
  6. Invalidation Level: Specific price level that would negate this scenario
Typical Scenario Framework
  • Base Case Scenario (40-60%): Most likely outcome based on current structure
  • Bull Case Scenario (20-40%): Optimistic scenario requiring upside breakout
  • Bear Case Scenario (20-40%): Pessimistic scenario requiring downside breakdown
  • Alternative Scenario (5-15%): Lower probability but technically plausible outcome

Adjust probabilities based on strength of supporting technical factors. Ensure probabilities are realistic and sum to 100%.

Step 5: Generate Analysis Report

For each chart analyzed, create a comprehensive markdown report using the template structure:

Read and use as template: assets/analysis_template.md

The report must include all sections:

  1. Chart Overview
  2. Trend Analysis
  3. Support and Resistance Levels
  4. Moving Average Analysis
  5. Volume Analysis
  6. Chart Patterns and Price Action
  7. Current Market Assessment
  8. Scenario Analysis (2-4 scenarios with probabilities)
  9. Summary
  10. Disclaimer

File Naming Convention: Save each analysis as [SYMBOL]_technical_analysis_[YYYY-MM-DD].md

Example: SPY_technical_analysis_2025-11-02.md

Step 6: Repeat for Multiple Charts

If multiple charts are provided:

  1. Complete the full analysis workflow (Steps 3-5) for the first chart
  2. Save the analysis report
  3. Proceed to the next chart
  4. Repeat until all charts have been analyzed and documented

Do not batch analyses. Complete and save each report before moving to the next chart.

Quality Standards

Objectivity Requirements
  • Base all analysis strictly on observable chart data
  • Avoid incorporating external information (news, fundamentals, sentiment)
  • Do not use subjective language like "I think" or "I feel"
  • Express uncertainty clearly when signals are ambiguous
  • Present both bullish and bearish possibilities to avoid confirmation bias
Completeness Requirements
  • Address all sections of the analysis template
  • Provide specific price levels for support, resistance, and targets
  • Justify probability estimates with technical factors
  • Include invalidation levels for each scenario
  • Note any limitations or caveats to the analysis
Clarity Requirements
  • Use precise technical terminology correctly
  • Write in clear, professional language
  • Structure information logically
  • Include specific price levels (not vague descriptions)
  • Make scenarios distinct and mutually exclusive

Example Usage Scenarios

Example 1: Single Chart Analysis

User: "Please analyze this weekly chart of the S&P 500"
[Provides chart image]

Analyst:
1. Confirms receipt of chart image
2. Reads technical_analysis_framework.md for methodology
3. Conducts systematic analysis (trend, S/R, MA, volume, patterns)
4. Develops 3 scenarios with probabilities (e.g., 55% bullish continuation, 30% consolidation, 15% reversal)
5. Generates comprehensive analysis report using template
6. Saves as SPY_technical_analysis_2025-11-02.md

Example 2: Multiple Chart Analysis

User: "Analyze these three charts: Bitcoin, Ethereum, and Nasdaq"
[Provides 3 chart images]

Analyst:
1. Confirms receipt of 3 charts
2. Reads technical_analysis_framework.md
3. Analyzes Bitcoin chart completely → Generates report → Saves as BTC_technical_analysis_2025-11-02.md
4. Analyzes Ethereum chart completely → Generates report → Saves as ETH_technical_analysis_2025-11-02.md
5. Analyzes Nasdaq chart completely → Generates report → Saves as NDX_technical_analysis_2025-11-02.md
6. Notifies user that all three analyses are complete

Example 3: Focused Analysis Request

User: "I'm particularly interested in whether this stock will break above resistance. Analyze the chart."
[Provides chart image]

Analyst:
1. Conducts full systematic analysis
2. Pays special attention to resistance levels and breakout probability
3. Develops scenarios with emphasis on breakout vs. rejection possibilities
4. Assigns probabilities based on volume, trend strength, and proximity to resistance
5. Generates complete report with focused scenario analysis

Contrarian Confirmation Mode (Shapiro Step 3)

This is an ADDITIVE mode, separate from the pure chart-analysis workflow above. It activates only on an explicit contrarian-confirmation request — typically after cot-contrarian-detector (step 1) has flagged a market crowded and, optionally, news-reaction-failure-analyzer (step 2) has shown it failed to react to favorable news. A plain "analyze this chart" request still runs the original workflow (Steps 1-6 above) unchanged.

Purpose

Confirm whether the WEEKLY chart is showing price-action evidence that a crowded market is reversing: a weekly key reversal, an intraweek failed extreme, or a confirmed-then-rejected failed breakout — vetoed by a continuation check (a new closing extreme in the crowd's direction more recent than any signal found). See references/contrarian-confirmation-checklist.md for the full, word-for-word methodology shared by both chart mode and script mode.

Show full SKILL.md (740 more words)Show less
Inputs
  • Crowd direction: CROWDED_LONG or CROWDED_SHORT — from the user, or from a prior cot-contrarian-detector report.
  • Chart image (primary): a user-supplied weekly chart, read the same way as the existing workflow, using the strict definitions below.
  • Script fallback (data-driven): scripts/check_weekly_price_action.py when no chart is supplied, or when an auditable, deterministic result is wanted instead of (or alongside) a visual read.
The Three Checks + Swing Levels
  1. Weekly key reversal: a new swing-lookback extreme (default 13 weeks) followed by a close through the prior week's opposite level.
  2. Failed extreme: an intraweek poke past the prior extreme-lookback level (default 52 weeks) that closes back through it the same week.
  3. Failed breakout: a weekly CLOSING breakout past the prior extreme-lookback level, rejected (closed back through) within <=3 subsequent weeks — week_of is the FAILURE week, never the breakout week.
  4. Continuation veto: a new CLOSING extreme in the crowd's direction, strictly more recent than the newest triggered signal above, vetoes confirmation regardless of what triggered.
  5. Swing levels: the nearest fractal swing high/low (5-week pivot, with a documented fallback) supplies stop_reference — the nearest swing high when fading a crowded LONG, the nearest swing low when fading a crowded SHORT.

Every comparison is a STRICT inequality; window truncation is per-evaluated-week, not per-run. Full definitions, the direction-mirror table, worked examples, and the confidence-HIGH rule are in references/contrarian-confirmation-checklist.md — read it before producing a chart-mode verdict, so chart and script judge identically.

Output Contract
yaml
symbol: BT
direction: CROWDED_LONG
mode: data # "chart" for a Claude chart-image read
verdict: CONFIRMED | NOT_CONFIRMED | INSUFFICIENT_DATA
confidence: HIGH | MEDIUM | LOW # LOW reserved, never emitted in v1
verdict_reason: key_reversal | failed_extreme | failed_breakout |
  continuation_intact | no_reversal_evidence |
  insufficient_weekly_bars | no_price_source | ...
checks:
  weekly_key_reversal:
    { triggered, week_of, swing_window_weeks_used,
      extreme_window_weeks_used, is_full_window_extreme, detail }
  failed_extreme: { triggered, attempted_level, week_of, window_weeks_used, detail }
  failed_breakout: { triggered, breakout_level, week_of, window_weeks_used, detail }
  continuation: { new_closing_extreme_with_crowd, week_of, window_weeks_used }
swing_levels:
  nearest_swing_high: { price, week_of, fallback }
  nearest_swing_low: { price, week_of, fallback }
  stop_reference: 0.0
weekly_bars_used: 52
last_completed_week: 2026-07-06
handoff: # consumed by contrarian-setup-gate (#241)
  price_action: { verdict, confidence, stop_reference, report_path }
run_context:
  {
    price_symbol,
    price_source,
    proxy_used,
    as_of,
    lookbacks,
    recency,
    min_weeks,
    detector_json,
    detector_age_days,
    schema_version,
  }

Invariant: checks (and swing_levels) is null whenever verdict: INSUFFICIENT_DATA — regardless of the specific reason (no_price_source, insufficient_weekly_bars, a detector-json refusal, ...). A downstream consumer can check verdict alone before deciding whether checks.* is safe to read, without branching on verdict_reason.

File naming: ta_confirmation_<SYMBOL>_<as-of>.json and ta_confirmation_<SYMBOL>_<as-of>.md, saved to reports/.

Chart-Primary, Script-Fallback

Chart images remain the PRIMARY input, consistent with this skill's identity. Run the script instead of (or alongside) a chart read when no chart is supplied, or when an auditable, deterministic result is preferred:

bash
python3 skills/technical-analyst/scripts/check_weekly_price_action.py \
  --symbol BT --direction CROWDED_LONG --as-of 2026-07-15 \
  --output-dir reports/

Or resolve direction from a cot-contrarian-detector report directly:

bash
python3 skills/technical-analyst/scripts/check_weekly_price_action.py \
  --symbol BT --detector-json reports/cot_crowding_2026-07-12.json \
  --as-of 2026-07-15 --output-dir reports/

The script fetches weekly-resampled OHLC via a documented futures-to-ETF fallback chain (see the module docstring in scripts/check_weekly_price_action.py), truncates daily bars to --as-of BEFORE resampling (no lookahead), and fails closed to INSUFFICIENT_DATA — never a crash — on an unreadable (missing file), syntactically invalid, stale, or structurally malformed --detector-json, too little price history (--min-weeks, default 30), or no usable price source.

Conservative Disagreement Rule

If both chart mode and script mode produce a result for the same symbol/direction and their verdicts DISAGREE, the final verdict is NOT_CONFIRMED (verdict_reason: mode_disagreement), with both sub-results attached for review — never silently prefer one mode. If one mode is INSUFFICIENT_DATA and the other is a clean verdict, the clean verdict stands.

Guardrails
  • Verdict-only — never a trade recommendation on its own. This confirms step 3 of 5 (Shapiro's process). Entry and exit planning are still manual and still required; position sizing belongs to position-sizer / futures-position-sizer, not this mode.
  • INSUFFICIENT_DATA never advances the pipeline — fail-closed on every degraded input, always exits 0 with a report written.
  • Weekly timeframe only.
  • The existing chart-analysis workflow above is unchanged — this mode only activates on an explicit contrarian-confirmation request.
  • A single-signal MEDIUM verdict is deliberately weak evidence — see the Confidence section of references/contrarian-confirmation-checklist.md.

Resources

This skill includes the following bundled resources:

references/technical_analysis_framework.md

Comprehensive methodology for technical analysis including:

  • Trend analysis criteria and classification
  • Support and resistance identification techniques
  • Moving average interpretation guidelines
  • Volume analysis principles
  • Chart pattern recognition
  • Scenario development and probability assignment framework
  • Objectivity and discipline reminders

Usage: Read this file before conducting analysis to ensure systematic, objective approach.

assets/analysis_template.md

Structured template for technical analysis reports with all required sections.

Usage: Use this template structure for every analysis report. Copy the format and populate with specific findings for each chart.

references/contrarian-confirmation-checklist.md

Full methodology for Contrarian Confirmation Mode (Shapiro Step 3): direction convention, window/truncation rules, the 3 signal checks + continuation veto, swing-level (fractal pivot) rules, verdict synthesis, confidence rules, the output contract, a chart-mode walkthrough, and the conservative disagreement rule.

Usage: Read this file before producing a Contrarian Confirmation Mode verdict — chart mode and scripts/check_weekly_price_action.py must judge identically, so the same strict definitions apply to both.

scripts/check_weekly_price_action.py

Data-driven fallback CLI for Contrarian Confirmation Mode. Fetches weekly-resampled OHLC (documented futures-to-ETF fallback chain, --as-of information cutoff applied before resampling), runs the 3 signal checks + continuation veto + swing-level detection, and writes ta_confirmation_<SYMBOL>_<as-of>.json/.md to reports/.

Usage: Run when no chart image is supplied, or when an auditable, deterministic result is wanted. See the Contrarian Confirmation Mode section above for invocation examples.

© tradermonty, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 9 other files (scripts, references, assets) in skills/technical-analyst of tradermonty/claude-trading-skills.

  • SKILL.md
  • assets/analysis_template.md
  • references/contrarian-confirmation-checklist.md
  • references/technical_analysis_framework.md
  • requirements.txt
  • scripts/check_weekly_price_action.py
  • scripts/tests/test_check_weekly_price_action.py
  • scripts/tests/test_skill_contract.py
  • scripts/tests/test_weekly_price_action.py
  • scripts/weekly_price_action.py

Open the folder on GitHubat commit eab8d5c

Used in 5 other repositories

We found 8 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 5 other GitHub owners. This page covers the copy in tradermonty/claude-trading-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Technical Analyst 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.

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Questions about Technical Analyst

What does Technical Analyst do?

This skill should be used when analyzing weekly price charts for stocks, stock indices, cryptocurrencies, or forex pairs. Technical Analyst is an agent skill from tradermonty/claude-trading-skills. This skill should be used when analyzing weekly price charts for stocks, stock indices, cryptocurrencies, or forex pairs.

When should I use Technical Analyst?

Technical Analyst fits situations like: the user provides chart images and requests technical analysis; trend identification; support/resistance levels; scenario planning.

How do I install Technical Analyst in Claude Code?

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

How do I install Technical Analyst in Codex?

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

Can I use Technical Analyst 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 tradermonty/claude-trading-skills --skill technical-analyst -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/technical-analyst, .gemini/skills/technical-analyst, .github/skills/technical-analyst and .opencode/skills/technical-analyst in your project.

What does Technical Analyst need to run?

Going by SKILL.md and its folder, Technical Analyst needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Technical Analyst access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Technical Analyst 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 Technical Analyst use?

Technical Analyst is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Technical Analyst use?

About 4.6k tokens (SKILL.md is roughly 18k 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 6.5k tokens, read only when the agent opens those files.

What are the alternatives to Technical Analyst?

Skills that share tags, products or a category with Technical Analyst: Polyclaw (chainstacklabs/polyclaw, 360 stars), Longbridge Research (helsome/folio, 269 stars), Stock Analysis (24mlight/StockClaw, 101 stars) and Swapper Deposit (swapperfinance/swapper-toolkit, 852 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Technical Analyst?

tradermonty (a GitHub user) maintains it in tradermonty/claude-trading-skills, which has 2,960 GitHub stars. The repository holds 74 skills in this directory. The repository was last updated on October 5, 2026.

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