Tencent SkillHub · Data Analysis

Tvscreener

Query TradingView screener data for HK, A-share, A-share ETF, and US symbols with deepentropy/tvscreener. Use for stock lookup, technical indicators (price/change/RSI/MACD/volume), symbol filtering, and custom field/filter-based market queries.

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Install for OpenClaw

Quick setup

Download the package from Yavira.
Extract the archive and review SKILL.md first.
Import or place the package into your OpenClaw setup.

Requirements

Target platform: OpenClaw
Install method: Manual import
Extraction: Extract archive
Prerequisites: OpenClaw
Primary doc: SKILL.md

Package facts

Download mode: Yavira redirect
Package format: ZIP package
Source platform: Tencent SkillHub
What's included: SKILL.md, references/README_USAGE.md, references/api/enums.md, references/api/fields.md, references/api/filters.md, references/api/screeners.md

Validation

Use the Yavira download entry.
Review SKILL.md after the package is downloaded.
Confirm the extracted package contains the expected setup assets.

Install with your agent

Agent handoff

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Trust & source

Release facts

Source: Tencent SkillHub
Verification: Indexed source record
Version: 1.0.0

Provenance

Publisher: Subway-chenyan
Source page: View original listing
Canonical URL: Open canonical page

Documentation

ClawHub primary doc Primary doc: SKILL.md 8 sections Open source page

tvscreener

Use this skill for market queries with simple scripts first, then native Python when needed.

Install

python3 -m pip install -U tvscreener Python must be >=3.10.

Quick commands (run from skill root)

Use Python 3.10+ in your preferred environment (venv/pyenv/system Python). # Preset single-symbol output (recommended) python3 scripts/query_symbol.py --symbol HKEX:700 --market HONGKONG # Custom query (fields + filters) bash scripts/run_query.sh \ --market CHINA \ --symbol SHSE:600519 \ --fields 'NAME,PRICE,CHANGE_PERCENT,VOLUME,RELATIVE_STRENGTH_INDEX_14,MACD_LEVEL_12_26,MACD_SIGNAL_12_26,MACD_HIST,SIMPLE_MOVING_AVERAGE_20,SIMPLE_MOVING_AVERAGE_50,SIMPLE_MOVING_AVERAGE_200,EXPONENTIAL_MOVING_AVERAGE_20,EXPONENTIAL_MOVING_AVERAGE_50,EXPONENTIAL_MOVING_AVERAGE_200,BOLLINGER_UPPER_BAND_20,BOLLINGER_LOWER_BAND_20,STOCHASTIC_PERCENTK_14_3_3,STOCHASTIC_PERCENTD_14_3_3,AVERAGE_TRUE_RANGE_14,MOVING_AVERAGES_RATING' \ --filter 'NAME=600519' # Field discovery python3 scripts/discover_fields.py --keyword macd --limit 20

Shell quoting notes

Wrap --fields and --filter in single quotes. If you use interval syntax like FIELD|60, quoting is mandatory to avoid shell pipe parsing.

Query rules

Core technical set (recommended): PRICE, CHANGE_PERCENT, VOLUME, RELATIVE_STRENGTH_INDEX_14, MACD_LEVEL_12_26, MACD_SIGNAL_12_26, MACD_HIST, SIMPLE_MOVING_AVERAGE_20/50/200, EXPONENTIAL_MOVING_AVERAGE_20/50/200, BOLLINGER_UPPER_BAND_20, BOLLINGER_LOWER_BAND_20, STOCHASTIC_PERCENTK_14_3_3, STOCHASTIC_PERCENTD_14_3_3, AVERAGE_TRUE_RANGE_14, MOVING_AVERAGES_RATING Interval fields syntax: FIELD|60 / FIELD|240 (example: RELATIVE_STRENGTH_INDEX_14|60) Current caveat: interval fields may fail in scripts/custom_query.py with FieldWithInterval attribute errors in some tvscreener versions. Workaround: run without interval fields, or use scripts/query_symbol.py for stable single-symbol technical snapshots. Filters: =, !=, >, <, >=, <=

Troubleshooting

ImportError: cannot import name 'Market' from 'tvscreener' Usually caused by mismatched Python/site-packages or multiple Python environments. Fix: ensure commands and installation use the same Python (3.10+), then reinstall: python3 -m pip install -U tvscreener zsh: command not found: 60,... Cause: unquoted FIELD|60 interpreted as shell pipes. Fix: single-quote the full --fields string.

References

Workflow + patterns: references/README_USAGE.md API details: references/api/screeners.md references/api/fields.md references/api/filters.md references/api/enums.md If scripts are insufficient, read references and write direct Python using tvscreener native API.

Regression test

bash scripts/test_markets.sh Covers Tencent (HK), Moutai (A), A-share ETF (510300), and BIDU (US).

Category context

Data access, storage, extraction, analysis, reporting, and insight generation.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package

6 Docs

SKILL.md Primary doc
references/api/enums.md Docs
references/api/fields.md Docs
references/api/filters.md Docs
references/api/screeners.md Docs
references/README_USAGE.md Docs