Agent skill

Scanner Bullish

by staskh in staskh/trading_skills

Scan stocks for bullish trends using technical indicators (SMA, RSI, MACD, ADX).

MITAuto-check passedBusiness, Finance & HR

Install Scanner Bullish

skills CLI
$ npx skills add staskh/trading_skills --skill scanner-bullish -a claude-code

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

GitHub CLI
$ gh skill install staskh/trading_skills scanner-bullish --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/staskh/trading_skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/scanner-bullish .claude/skills/scanner-bullish && 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
scanner-bullish
GitHub stars
375
Token cost
~983 tokens
SKILL.md length
407 words
Files
2 (incl. scripts)
Skills in repo
28
Repo updated
First seen
Licence
MIT

At a glance

Scan stocks for bullish trends using technical indicators (SMA, RSI, MACD, ADX).

  • User asks to scan for bullish stocks
  • SKILL.md covers Instructions, Arguments, Scoring System (max ~9.5 points) and Output, plus 6 more sections
  • Runs Python scripts from its folder; calls uv
  • Find trending stocks

What it does

Scanner Bullish is an agent skill from staskh/trading_skills. Scan stocks for bullish trends using technical indicators (SMA, RSI, MACD, ADX). Use when user asks to scan for bullish stocks, find trending stocks, or rank symbols by momentum.

Its SKILL.md is about 980 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including scripts (for example `scripts/scan.py`).

It sits in Business, Finance & HR. The repository describes itself as: Claude powered advisor system for option traders. The licence is MIT.

When your agent uses it

  • User asks to scan for bullish stocks
  • Find trending stocks
  • Rank symbols by momentum

Example prompts

  • “/scanner-bullish”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit b71a74f. 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:

    • uv

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

  • Network

    No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.

    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

Scanner Bullish loads about 983 tokens when it runs. Until then it costs about 49 tokens; SKILL.md has 407 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~49
When it runs · the whole SKILL.md, loaded when a task matches
~983

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 staskh/trading_skills at commit b71a74f, republished under its MIT licence (© staskh). 407 words, ~983 tokens.

Download SKILL.mdSave it as .claude/skills/scanner-bullish/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
scanner-bullish
description
Scan stocks for bullish trends using technical indicators (SMA, RSI, MACD, ADX). Use when user asks to scan for bullish stocks, find trending stocks, or rank symbols by momentum.
dependencies
trading-skills

Bullish Scanner

Scans symbols for bullish trends and ranks them by composite score.

Instructions

Note: If uv is not installed or pyproject.toml is not found, replace uv run python with python in all commands below.

bash
uv run python scripts/scan.py SYMBOLS [--top N] [--period PERIOD]

Arguments

  • SYMBOLS - Comma-separated ticker symbols (e.g., AAPL,MSFT,GOOGL,NVDA)
  • --top - Number of top results to return (default: 30)
  • --period - Historical period for analysis: 1mo, 3mo, 6mo (default: 3mo)

Scoring System (max ~9.5 points)

IndicatorConditionPoints
SMA20Price > SMA20+1.0
SMA50Price > SMA50+1.0
RSI50-70 (bullish)+1.0
30-50 (neutral)+0.5
<30 (oversold)+0.25
MACDMACD > Signal+1.0
Histogram rising+0.5
EMA9/21EMA9 > EMA21 (golden cross)+0.5
EMA9 < EMA21 (death cross)-0.25
Dual crossoverBoth up, both ≤10 days+1.0
Both up, any age+0.5
Both down, both ≤10 days-1.0
Both down, any age-0.5
Directions conflict-0.5
ADX>25 with +DI > -DI+1.5
+DI > -DI only+0.5
Momentumperiod return / 20-1 to +2

Output

Returns JSON with:

  • scan_date - Timestamp of scan
  • symbols_scanned - Total symbols analyzed
  • results - Array sorted by score (highest first):
    • symbol, score, price
    • next_earnings, earnings_timing (BMO/AMC)
    • period_return_pct, pct_from_sma20, pct_from_sma50
    • rsi, macd, macd_signal, macd_hist, adx, dmp, dmn
    • ema9, ema21 — current EMA9 and EMA21 values
    • ema_crossover - Most recent EMA9/EMA21 crossover (or null if none found):
      • direction - "up" (EMA9 crossed above EMA21 = bullish) or "down" (crossed below = bearish)
      • days_ago - Trading days since the crossover bar (0 = happened in the most recent bar)
    • macd_crossover - Most recent MACD crossover (or null if none found):
      • direction - "up" (MACD crossed above signal = bullish) or "down" (crossed below = bearish)
      • days_ago - Trading days since the crossover bar (0 = happened in the most recent bar)
    • signals - List of triggered conditions
Show full SKILL.md (139 more words)Show less

EMA Crossover Interpretation

  • EMA9 > EMA21 with small days_ago (0-5): fresh golden cross — short-term momentum confirmed
  • EMA9 just crossed below EMA21: death cross — short-term momentum turning negative
  • EMA9 crossover lagging MACD crossover by days: normal — MACD leads, EMA confirms
  • null: EMA9/21 relationship unchanged throughout the period

MACD Crossover Interpretation

  • direction: "up" with small days_ago (0-5): fresh bullish crossover — early entry signal
  • direction: "up" from a deeply negative signal: recovery from correction
  • direction: "down": momentum has turned bearish regardless of score
  • null: no sign change found in the period — trend has been consistently one-directional

Examples

bash
# Scan a few symbols
uv run python scripts/scan.py AAPL,MSFT,GOOGL,NVDA,TSLA

# Get top 10 from larger list
uv run python scripts/scan.py AAPL,MSFT,GOOGL,NVDA,TSLA,AMD,AMZN,META --top 10

# Use 6-month lookback
uv run python scripts/scan.py AAPL,MSFT,GOOGL --period 6mo

Interpretation

  • Score > 6: Strong bullish trend
  • Score 4-6: Moderate bullish
  • Score 2-4: Neutral/weak
  • Score < 2: Bearish or no trend

Dependencies

  • pandas
  • pandas-ta
  • yfinance

Timezone

All timestamps and time-based calculations must use the America/New_York timezone. All JSON output must include generated_at (NY time string) and data_delay fields.

© staskh, 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 1 other file (scripts) in .claude/skills/scanner-bullish of staskh/trading_skills.

  • SKILL.md
  • scripts/scan.py

Open the folder on GitHubat commit b71a74f

Compare with similar skills

Scanner Bullish 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.

Scanner Bullish compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Scanner Bullish this skillstaskh/trading_skills375—~983Automated safety check: PassMIT
Technical Analysttradermonty/claude-trading-skills3k4 repos~4.6kAutomated safety check: PassMIT
Theme Detectortradermonty/claude-trading-skills3k2 repos~4.9kAutomated safety check: PassMIT
Creating Financial ModelsChen-zexi/open-ptc-agent7293 repos~1.3kAutomated safety check: PassMIT
Stock APIzhangxiangliang/stock-api2k—~507Automated safety check: PassMIT
Itr Walakaranb192/itr-wala871—~3.6kAutomated safety check: PassMIT

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Questions about Scanner Bullish

What does Scanner Bullish do?

Scan stocks for bullish trends using technical indicators (SMA, RSI, MACD, ADX). Scanner Bullish is an agent skill from staskh/trading_skills. Scan stocks for bullish trends using technical indicators (SMA, RSI, MACD, ADX).

When should I use Scanner Bullish?

Scanner Bullish fits situations like: user asks to scan for bullish stocks; find trending stocks; rank symbols by momentum.

How do I install Scanner Bullish in Claude Code?

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

How do I install Scanner Bullish in Codex?

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

Can I use Scanner Bullish 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 staskh/trading_skills --skill scanner-bullish -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/scanner-bullish, .gemini/skills/scanner-bullish, .github/skills/scanner-bullish and .opencode/skills/scanner-bullish in your project.

What does Scanner Bullish need to run?

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

Does Scanner Bullish access the network?

SKILL.md contains no URLs. Its commands use uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Scanner Bullish 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 Scanner Bullish use?

Scanner Bullish 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 Scanner Bullish use?

About 983 tokens (SKILL.md is roughly 3.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Scanner Bullish?

Skills that share tags, products or a category with Scanner Bullish: Technical Analyst (tradermonty/claude-trading-skills, 3k stars), Theme Detector (tradermonty/claude-trading-skills, 3k stars), Creating Financial Models (Chen-zexi/open-ptc-agent, 729 stars) and Stock API (zhangxiangliang/stock-api, 2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Scanner Bullish?

staskh (a GitHub user) maintains it in staskh/trading_skills, which has 375 GitHub stars. The repository holds 28 skills in this directory. The repository was last updated on September 28, 2026.

Source: staskh/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.