Tencent SkillHub · Developer Tools

A股短线交易决策 A Share Short Term Decision

A-share short-term trading decision skill for 1-5 day horizon. Use when you need market sentiment, sector rotation, strong stock scanning, capital flow confi...

skill openclawclawhub Free

0 Downloads

0 Stars

0 Installs

0 Score

High Signal

A-share short-term trading decision skill for 1-5 day horizon. Use when you need market sentiment, sector rotation, strong stock scanning, capital flow confi...

⬇ 0 downloads ★ 0 stars Unverified but indexed

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: README.md, SKILL.md, config.json, main.py, prompts/analysis_prompt.txt, requirements.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

Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.

Download the package from Yavira.
Extract it into a folder your agent can access.
Paste one of the prompts below and point your agent at the extracted folder.

New install

I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.

Upgrade existing

I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.

Open Send to Agent page Open JSON manifest Open Markdown brief

Trust & source

Release facts

Source: Tencent SkillHub
Verification: Indexed source record
Version: 1.2.0

Provenance

Publisher: kenera
Source page: View original listing
Canonical URL: Open canonical page

Documentation

ClawHub primary doc Primary doc: SKILL.md 7 sections Open source page

A-Share Short-Term Decision Skill

Implement in sequence: Run short_term_signal_engine(analysis_date) for target date. If needed, persist prediction with run_prediction_for_date(analysis_date). Compare prediction vs actual market with compare_prediction_with_market(prediction_date, actual_date). Output report with generate_daily_report(analysis_date).

short_term_signal_engine(analysis_date=None)

analysis_date: YYYY-MM-DD or YYYYMMDD Returns weighted short-term score and recommendation status. Always returns friendly no_recommendation_message when no tradable candidate exists.

run_prediction_for_date(analysis_date)

Runs signal engine for the specified date. Appends decision snapshot into data/decision_log.jsonl.

compare_prediction_with_market(prediction_date, actual_date=None)

Loads prediction from log (or auto-generates if missing). Compares predicted candidates against real market closes on actual_date. Returns per-stock return and summary statistics.

No-Recommendation Behavior

Required behavior: Never return empty output. If candidates is empty or signal is NO_TRADE, explicitly say: 当前暂无可执行短线买入标的. Include reason and next action.

Runtime

python3 main.py short_term_signal_engine --date 2026-02-12 python3 main.py run_prediction_for_date --date 2026-02-12 python3 main.py compare_prediction_with_market --prediction-date 2026-02-12 --actual-date 2026-02-13 python3 main.py generate_daily_report --date 2026-02-12

Subskills Workflow

For recurring optimize-then-recommend flow, run: python3 subskills/config-optimization/optimize_from_aggressive.py --analysis-period "2026-02-01 to 2026-02-12" python3 subskills/daily-recommendation/generate_daily_recommendation.py --date 2026-02-14 All generated artifacts are stored under data/.

Category context

Code helpers, APIs, CLIs, browser automation, testing, and developer operations.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package

3 Docs1 Scripts1 Config1 Assets

SKILL.md Primary doc
README.md Docs
requirements.md Docs
main.py Scripts
config.json Config
prompts/analysis_prompt.txt Assets