Tushare Data
zillionare/zillionare
面向中文自然语言的 Tushare 数据研究技能。用于把“看看这只股票最近怎么样”“帮我查财报趋势”“最近哪个板块最强”“北向资金在买什么”“给我导出一份行情数据”这类请求，转成可执行的数据获取、清洗、对比、筛选、导出与简要分析流程。适用于 A 股、指数、ETF/基金、财务、估值、资金流、公告新闻、板块概念与宏观数据等研究场景。
Screen S&P 500 stocks for Mark Minervini's Volatility Contraction Pattern (VCP) and detect historical VCPs in a single ticker's price path.
Install Vcp Screener
$ npx skills add tradermonty/claude-trading-skills --skill vcp-screener -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install tradermonty/claude-trading-skills vcp-screener --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/tradermonty/claude-trading-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/vcp-screener .claude/skills/vcp-screener && rm -rf skills-srcUse ~/.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/
Install the "vcp-screener" agent skill from https://github.com/tradermonty/claude-trading-skills/tree/main/skills/vcp-screener into .claude/skills/vcp-screener/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vcp-screener", 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 install https://github.com/tradermonty/claude-trading-skills/tree/main/skills/vcp-screenerType 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.
$ npx skills add tradermonty/claude-trading-skills --skill vcp-screener -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install tradermonty/claude-trading-skills vcp-screener --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tradermonty/claude-trading-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/vcp-screener .agents/skills/vcp-screener && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "vcp-screener" agent skill from https://github.com/tradermonty/claude-trading-skills/tree/main/skills/vcp-screener into .agents/skills/vcp-screener/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vcp-screener", 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.
$ npx skills add tradermonty/claude-trading-skills --skill vcp-screener -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install tradermonty/claude-trading-skills vcp-screener --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tradermonty/claude-trading-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/vcp-screener .cursor/skills/vcp-screener && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "vcp-screener" agent skill from https://github.com/tradermonty/claude-trading-skills/tree/main/skills/vcp-screener into .cursor/skills/vcp-screener/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vcp-screener", 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 https://github.com/tradermonty/claude-trading-skills.git --path skills/vcp-screener--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add tradermonty/claude-trading-skills --skill vcp-screener -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install tradermonty/claude-trading-skills vcp-screener --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tradermonty/claude-trading-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/vcp-screener .gemini/skills/vcp-screener && rm -rf skills-srcUse ~/.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/
Install the "vcp-screener" agent skill from https://github.com/tradermonty/claude-trading-skills/tree/main/skills/vcp-screener into .gemini/skills/vcp-screener/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vcp-screener", 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.
$ gh skill install tradermonty/claude-trading-skills vcp-screenerInstalls 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).
$ npx skills add tradermonty/claude-trading-skills --skill vcp-screener -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/tradermonty/claude-trading-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/vcp-screener .github/skills/vcp-screener && rm -rf skills-srcUse ~/.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/
Install the "vcp-screener" agent skill from https://github.com/tradermonty/claude-trading-skills/tree/main/skills/vcp-screener into .github/skills/vcp-screener/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vcp-screener", 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.
$ npx skills add tradermonty/claude-trading-skills --skill vcp-screener -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install tradermonty/claude-trading-skills vcp-screener --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tradermonty/claude-trading-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/vcp-screener .opencode/skills/vcp-screener && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "vcp-screener" agent skill from https://github.com/tradermonty/claude-trading-skills/tree/main/skills/vcp-screener into .opencode/skills/vcp-screener/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vcp-screener", 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
vcp-screener- GitHub stars
- 3k
- Used in
- 1 other repo
- Token cost
- ~2k tokens
- SKILL.md length
- 681 words
- Files
- 27 (incl. scripts, references)
- Skills in repo
- 74
- Repo updated
- First seen
- Licence
- MIT
At a glance
Screen S&P 500 stocks for Mark Minervini's Volatility Contraction Pattern (VCP) and detect historical VCPs in a single ticker's price path.
- Works in 4 steps: Prepare and Execute Screening → Review Results → Present Analysis → …
- User requests VCP screening
- SKILL.md covers When to Use, Prerequisites, Workflow and 3-Phase Pipeline, plus 2 more sections
- Runs Python scripts from its folder; calls python3; needs FMP_API_KEY
What it does
Vcp Screener is an agent skill from tradermonty/claude-trading-skills. Screen S&P 500 stocks for Mark Minervini's Volatility Contraction Pattern (VCP) and detect historical VCPs in a single ticker's price path. Identifies Stage 2 uptrend stocks forming tight bases with contracting volatility near breakout pivot points; in historical single-ticker mode walks a multi-year history and emits every VCP that formed with forward-outcome stats (breakout / stop-hit / timeout). Use when user requests VCP screening, Minervini-style setups, tight base patterns, volatility contraction breakout…
Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 29 other files, including scripts and reference files (for example `references/fmp_api_endpoints.md`, `references/scoring_system.md` and `references/vcp_methodology.md`).
It sits in Business, Finance & HR, covering Trading and backtesting. 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
- User requests VCP screening
- Minervini-style setups
- Tight base patterns
- Volatility contraction breakout candidates
Example prompts
- “/vcp-screener”
Requirements
- Python 3
- A credential in FMP_API_KEY
Workflow steps
4 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit c8d58f0. 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 13 files in scripts/ (Python, from the files we listed), 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 these keys or tokens, usually read from environment variables:
FMP_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Vcp Screener loads about 2k tokens when it runs, and up to ~6k if it reads all its reference files. Until then it costs about 161 tokens; SKILL.md has 681 words of instructions outside code blocks.
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 c8d58f0, republished under its MIT licence (© tradermonty). 681 words, ~1,976 tokens.
Download SKILL.mdSave it as
.claude/skills/vcp-screener/SKILL.md (or your agent's skills folder). This skill also uses 26 other files; get the full folder from GitHub.- name
- vcp-screener
- description
- Screen S&P 500 stocks for Mark Minervini's Volatility Contraction Pattern (VCP) and detect historical VCPs in a single ticker's price path. Identifies Stage 2 uptrend stocks forming tight bases with contracting volatility near breakout pivot points; in historical single-ticker mode walks a multi-year history and emits every VCP that formed with forward-outcome stats (breakout / stop-hit / timeout). Use when user requests VCP screening, Minervini-style setups, tight base patterns, volatility contraction breakout candidates, Stage 2 momentum stock scanning, or historical VCP pattern study on a specific ticker (e.g. FIX, TSLA).
VCP Screener - Minervini Volatility Contraction Pattern
Screen S&P 500 stocks for Mark Minervini's Volatility Contraction Pattern (VCP), identifying Stage 2 uptrend stocks with contracting volatility near breakout pivot points.
When to Use
- User asks for VCP screening or Minervini-style setups
- User wants to find tight base / volatility contraction patterns
- User requests Stage 2 momentum stock scanning
- User asks for breakout candidates with defined risk
- User asks "find every historical VCP in
<TICKER>" or wants to study one ticker's past VCP setups with forward outcomes (--history --ticker SYM)
Prerequisites
- FMP API key (set
FMP_API_KEYenvironment variable or pass--api-key) - Free tier (250 calls/day) is sufficient for default screening (top 100 candidates)
- Paid tier recommended for full S&P 500 screening (
--full-sp500)
Workflow
Step 1: Prepare and Execute Screening
Run the VCP screener script:
# Default: S&P 500, top 100 candidates
python3 skills/vcp-screener/scripts/screen_vcp.py --output-dir skills/vcp-screener/scripts
# Custom universe
python3 skills/vcp-screener/scripts/screen_vcp.py --universe AAPL NVDA MSFT AMZN META --output-dir skills/vcp-screener/scripts
# Full S&P 500 (paid API tier)
python3 skills/vcp-screener/scripts/screen_vcp.py --full-sp500 --output-dir skills/vcp-screener/scriptsStrict Mode (Minervini pure setup)
Only return stocks with valid_vcp=True AND execution_state in (Pre-breakout, Breakout):
python3 skills/vcp-screener/scripts/screen_vcp.py --strict --output-dir reports/Historical single-ticker mode
Walk one ticker's multi-year history, detect every VCP that ever formed, and attach forward-outcome stats (breakout / stop-hit / timeout, days-to-outcome, max gain, max loss) per detection. Useful for pattern study and backtesting context — not a real-time screener.
# Default: scan ~5 years (1260 trading days), 5-day stride, 60-day outcome window
python3 skills/vcp-screener/scripts/screen_vcp.py \
--history --ticker FIX --output-dir reports/
# Custom scan length: 750 trading days (~3 years), 90-day outcome window
python3 skills/vcp-screener/scripts/screen_vcp.py \
--history 750 --ticker TSLA \
--stride-days 5 --outcome-days 90 \
--output-dir reports/
# Long scan: 10 years (2520 trading days)
python3 skills/vcp-screener/scripts/screen_vcp.py \
--history 2520 --ticker NVDA --output-dir reports/Outputs (timestamped):
vcp_history_<SYM>_<YYYY-MM-DD_HHMMSS>.json— timeline of detections with full analyzer payload +forward_outcomeper detection + summary stats.vcp_history_<SYM>_<YYYY-MM-DD_HHMMSS>.md— human-readable timeline.
Mode-specific flags:
| Parameter | Default | Range | Effect |
|---|---|---|---|
--history [DAYS] | (off) / 1260 if bare | 100-5040 | Enable historical mode; optionally specify trading-day scan window (requires --ticker) |
--ticker SYM | — | — | Ticker to scan |
--stride-days | 5 | 1-60 | Trading-day step between as-of cursor positions |
--outcome-days | 60 | 5-252 | Forward window evaluated per detection |
Notes:
- Two FMP API calls per scan (ticker + SPY history), not 100+ like the cross-sectional pipeline.
marketCapand absolute RS percentile reflect the ticker in isolation, not against the live screening universe — use this report for pattern study, not portfolio sizing.- Detections are deduplicated by
(T1_high_date, last_low_date, pivot)so the same VCP isn't reported repeatedly as the cursor ages.
Advanced Tuning (for backtesting)
Adjust VCP detection parameters for research and backtesting:
python3 skills/vcp-screener/scripts/screen_vcp.py \
--min-contractions 3 \
--t1-depth-min 12.0 \
--breakout-volume-ratio 2.0 \
--trend-min-score 90 \
--atr-multiplier 1.5 \
--output-dir reports/| Parameter | Default | Range | Effect |
|---|---|---|---|
--min-contractions | 2 | 2-4 | Higher = fewer but higher-quality patterns |
--t1-depth-min | 10.0% | 1-50 | Higher = excludes shallow first corrections |
--breakout-volume-ratio | 1.5x | 0.5-10 | Higher = stricter volume confirmation |
--trend-min-score | 85 | 0-100 | Higher = stricter Stage 2 filter |
--atr-multiplier | 1.5 | 0.5-5 | Lower = more sensitive swing detection |
--contraction-ratio | 0.70 | 0.1-1 | Lower = requires tighter contractions |
--min-contraction-days | 5 | 1-30 | Higher = longer minimum contraction |
--lookback-days | 120 | 30-365 | Longer = finds older patterns |
--max-sma200-extension | 50.0% | — | SMA200 distance threshold for Overextended state and penalty |
--wide-and-loose-threshold | 15.0% | — | Final contraction depth above which wide-and-loose flag triggers |
--strict | off | — | Minervini strict mode: only Pre-breakout or Breakout with valid VCP |
Show full SKILL.md (266 more words)Show less
Step 2: Review Results
- Read the generated JSON and Markdown reports
- Load
references/vcp_methodology.mdfor pattern interpretation context - Load
references/scoring_system.mdfor score threshold guidance
Step 3: Present Analysis
For each top candidate, present:
- Quality (
composite_score/ rating) — how well-formed is the VCP pattern? - Execution State (
execution_state) — is it buyable now? (Pre-breakout / Breakout = actionable) - Pattern Type (
pattern_type) — Textbook VCP / VCP-adjacent / Post-breakout / Extended Leader / Damaged ★marker if a State Cap was applied (raw score was downgraded)- Contraction details (T1/T2/T3 depths and ratios)
- Trade setup: pivot price, stop-loss, risk percentage
- Volume dry-up ratio and breakout_volume_score
- Relative strength rank
Step 4: Provide Actionable Guidance
By Execution State (primary filter):
- Pre-breakout / Breakout: Pattern is in the active entry window — apply rating-based sizing
- Early-post-breakout: Breakout underway but above ideal entry — reduced size or wait for pullback
- Extended / Overextended: Trade missed — add to watchlist for next base
- Damaged / Invalid: Setup invalidated — do not enter
By Rating (secondary, after state confirms actionability):
- Textbook VCP (90+): Buy at pivot with aggressive sizing (1.5-2x)
- Strong VCP (80-89): Buy at pivot with standard sizing (1x)
- Good VCP (70-79): Buy on volume confirmation above pivot (0.75x)
- Developing (60-69): Add to watchlist, wait for tighter contraction
- Weak/No VCP (<60): Monitor only or skip
3-Phase Pipeline
- Pre-Filter - Quote-based screening (price, volume, 52w position) ~101 API calls
- Trend Template - 7-point Stage 2 filter with 260-day histories ~100 API calls
- VCP Detection - Pattern analysis, scoring, report generation (no additional API calls)
Output
vcp_screener_YYYY-MM-DD_HHMMSS.json- Structured resultsvcp_screener_YYYY-MM-DD_HHMMSS.md- Human-readable report
Resources
references/vcp_methodology.md- VCP theory and Trend Template explanationreferences/scoring_system.md- Scoring thresholds and component weightsreferences/fmp_api_endpoints.md- API endpoints and rate limits
© 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 26 other files (scripts, references) in skills/vcp-screener of tradermonty/claude-trading-skills.
- SKILL.md
- references/fmp_api_endpoints.md
- references/scoring_system.md
- references/vcp_methodology.md
- requirements.txt
- scripts/_fmp_compat.py
- scripts/calculators/__init__.py
- scripts/calculators/execution_state.py
- scripts/calculators/forward_outcome.py
- scripts/calculators/pattern_classifier.py
- scripts/calculators/pivot_proximity_calculator.py
- scripts/calculators/relative_strength_calculator.py
- scripts/calculators/trend_template_calculator.py
- scripts/calculators/vcp_pattern_calculator.py
- scripts/calculators/volume_pattern_calculator.py
- scripts/fmp_client.py
- scripts/historical_report.py
- scripts/historical_scanner.py
- … and 9 more
Open the folder on GitHubat commit c8d58f0
Used in 1 other repository
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in tradermonty/claude-trading-skills, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Vcp Screener 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Vcp Screener this skilltradermonty/claude-trading-skills | 3k | 1 repos | ~2k | Automated safety check: Pass | MIT | |
| Tushare Datazillionare/zillionare | 322 | 2 repos | ~2.3k | Automated safety check: Pass | None | |
| Tradingview MCPatilaahmettaner/tradingview-mcp | 5k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Digital Oraclekomako-workshop/digital-oracle | 878 | — | ~5.9k | Automated safety check: Pass | MIT | |
| Polyclawchainstacklabs/polyclaw | 359 | 1 repos | ~2k | Automated safety check: Pass | Apache-2.0 | |
| Markdownfacioquo/stock-indicators-dotnet | 1.2k | — | ~812 | Automated safety check: Pass | Apache-2.0 |
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Questions about Vcp Screener
What does Vcp Screener do?
Screen S&P 500 stocks for Mark Minervini's Volatility Contraction Pattern (VCP) and detect historical VCPs in a single ticker's price path. Vcp Screener is an agent skill from tradermonty/claude-trading-skills. Screen S&P 500 stocks for Mark Minervini's Volatility Contraction Pattern (VCP) and detect historical VCPs in a single ticker's price path.
When should I use Vcp Screener?
Vcp Screener fits situations like: user requests VCP screening; minervini-style setups; tight base patterns; volatility contraction breakout candidates.
How do I install Vcp Screener in Claude Code?
Run `npx skills add tradermonty/claude-trading-skills --skill vcp-screener -a claude-code`. Or copy the skill folder (skills/vcp-screener in tradermonty/claude-trading-skills) into .claude/skills/vcp-screener in your project. Claude Code loads it when a task matches its description.
How do I install Vcp Screener in Codex?
Run `npx skills add tradermonty/claude-trading-skills --skill vcp-screener -a codex`. Or copy the skill folder (skills/vcp-screener in tradermonty/claude-trading-skills) into .agents/skills/vcp-screener in your project. Codex loads it when a task matches its description.
Can I use Vcp Screener 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 vcp-screener -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/vcp-screener, .gemini/skills/vcp-screener, .github/skills/vcp-screener and .opencode/skills/vcp-screener in your project.
What does Vcp Screener need to run?
Going by SKILL.md and its folder, Vcp Screener needs Python for the scripts in its folder, the command-line tools its instructions call (python3) and credentials named FMP_API_KEY. Our summary lists: Python 3; A credential in FMP_API_KEY.
Does Vcp Screener 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 Vcp Screener 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 Vcp Screener use?
Vcp Screener 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 Vcp Screener use?
About 2k tokens (SKILL.md is roughly 7.9k 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 4k tokens, read only when the agent opens those files.
What are the alternatives to Vcp Screener?
Skills that share tags, products or a category with Vcp Screener: Tushare Data (zillionare/zillionare, 322 stars), Tradingview MCP (atilaahmettaner/tradingview-mcp, 5k stars), Digital Oracle (komako-workshop/digital-oracle, 878 stars) and Polyclaw (chainstacklabs/polyclaw, 359 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Vcp Screener?
tradermonty (a GitHub user) maintains it in tradermonty/claude-trading-skills, which has 2,982 GitHub stars. The repository holds 74 skills in this directory. The repository was last updated on October 11, 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.