跳到正文
cccskills
免费在 GitHub 公开

edge-candidate-agent

Turn daily US stock prices, trading volume, and market hypotheses into prioritized research tickets for buying strategies. Export supported candidates as strategy files and check compatibility before handing them to trade-strategy-pipeline for historical testing.

中文简介正在准备中。当前显示英语简介。

原文查看原文说明

Generate and prioritize US equity long-side edge research tickets from EOD observations, then export pipeline-ready candidate specs for trade-strategy-pipeline Phase I. Use when users ask to turn hypotheses/anomalies into reproducible research tickets, convert validated ideas into `strategy.yaml` + `metadata.json`, or preflight-check interface compatibility (`edge-finder-candidate/v1`) before running pipeline backtests.

实测评分 未实测

查看安装方法

适用场景

  • Turning market observations into reproducible research tickets
  • Finding strategy candidates in daily price and volume data
  • Exporting supported ideas as strategy.yaml and metadata.json
  • Checking candidate compatibility before pipeline backtests

包含的文件(21)

  • SKILL.md5.7 KB
  • agents/openai.yaml282 B
  • references/ideation_loop.md1.3 KB
  • references/pipeline_if_v1.md1.6 KB
  • references/research_ticket_schema.md1.2 KB
  • references/signal_mapping.md1.2 KB
  • requirements.txt238 B
  • scripts/auto_detect_candidates.py68.3 KB
  • scripts/candidate_contract.py7.8 KB
  • scripts/export_candidate.py11.5 KB
  • scripts/tests/conftest.py148 B
  • scripts/tests/synthetic_ohlcv.py4.3 KB
  • scripts/tests/test_auto_detect_candidates.py8.4 KB
  • scripts/tests/test_auto_detect_dataframes.py24.8 KB
  • scripts/tests/test_auto_detect_main.py16.3 KB
  • scripts/tests/test_auto_detect_units.py13.5 KB
  • scripts/tests/test_candidate_contract.py7.0 KB
  • scripts/tests/test_contract_export_validate_edges.py14.3 KB
  • scripts/tests/test_export_candidate.py7.5 KB
  • scripts/tests/test_validate_candidate.py7.4 KB
  • scripts/validate_candidate.py4.9 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Edge Candidate Agent

Overview

Convert daily market observations into reproducible research tickets and Phase I-compatible candidate specs. Prioritize signal quality and interface compatibility over aggressive strategy proliferation. This skill can run end-to-end standalone, but in the split workflow it primarily serves the final export/validation stage.

When to Use

  • Convert market observations, anomalies, or hypotheses into structured research tickets.
  • Run daily auto-detection to discover new edge candidates from EOD OHLCV and optional hints.
  • Export validated tickets as strategy.yaml + metadata.json for trade-strategy-pipeline Phase I.
  • Run preflight compatibility checks for edge-finder-candidate/v1 before pipeline execution.

Prerequisites

  • Python 3.9+ with PyYAML installed.
  • Access to the target trade-strategy-pipeline repository for schema/stage validation.
  • uv available when running pipeline-managed validation via --pipeline-root.

Output

  • strategies/<candidate_id>/strategy.yaml: Phase I-compatible strategy spec.
  • strategies/<candidate_id>/metadata.json: provenance metadata including interface version and ticket context.
  • Validation status from scripts/validate_candidate.py (pass/fail + reasons).
  • Daily detection artifacts:
    • daily_report.md
    • market_summary.json
    • anomalies.json
    • watchlist.csv
    • tickets/exportable/*.yaml
    • tickets/research_only/*.yaml

Position in Split Workflow

Recommended split workflow:

  1. skills/edge-hint-extractor: observations/news -> hints.yaml
  2. skills/edge-concept-synthesizer: tickets/hints -> edge_concepts.yaml
  3. skills/edge-strategy-designer: concepts -> strategy_drafts + exportable ticket YAML
  4. skills/edge-candidate-agent (this skill): export + validate for pipeline handoff

Workflow

  1. Run auto-detection from EOD OHLCV:
    • skills/edge-candidate-agent/scripts/auto_detect_candidates.py
    • Optional: --hints for human ideation input
    • Optional: --llm-ideas-cmd for external LLM ideation loop
  2. Load the contract and mapping references:
    • references/pipeline_if_v1.md
    • references/signal_mapping.md
    • references/research_ticket_schema.md
    • references/ideation_loop.md
  3. Build or update a research ticket using references/research_ticket_schema.md.
  4. Export candidate artifacts with skills/edge-candidate-agent/scripts/export_candidate.py.
  5. Validate interface and Phase I constraints with skills/edge-candidate-agent/scripts/validate_candidate.py.
  6. Hand off candidate directory to trade-strategy-pipeline and run dry-run first.

Quick Commands

Daily auto-detection (with optional export/validation):

python3 skills/edge-candidate-agent/scripts/auto_detect_candidates.py \
  --ohlcv /path/to/ohlcv.parquet \
  --output-dir reports/edge_candidate_auto \
  --top-n 10 \
  --hints path/to/hints.yaml \
  --export-strategies-dir /path/to/trade-strategy-pipeline/strategies \
  --pipeline-root /path/to/trade-strategy-pipeline

Create a candidate directory from a ticket:

python3 skills/edge-candidate-agent/scripts/export_candidate.py \
  --ticket path/to/ticket.yaml \
  --strategies-dir /path/to/trade-strategy-pipeline/strategies

Validate interface contract only:

python3 skills/edge-candidate-agent/scripts/validate_candidate.py \
  --strategy /path/to/trade-strategy-pipeline/strategies/my_candidate_v1/strategy.yaml

Validate both interface contract and pipeline schema/stage rules:

python3 skills/edge-candidate-agent/scripts/validate_candidate.py \
  --strategy /path/to/trade-strategy-pipeline/strategies/my_candidate_v1/strategy.yaml \
  --pipeline-root /path/to/trade-strategy-pipeline \
  --stage phase1

Export Rules

  • Keep validation.method: full_sample.
  • Keep validation.oos_ratio omitted or null.
  • Export only supported entry families for v1:
    • pivot_breakout with vcp_detection
    • gap_up_continuation with gap_up_detection
  • Mark unsupported hypothesis families as research-only in ticket notes, not as export candidates.

Guardrails

  • Reject candidates that violate schema bounds (risk, exits, empty conditions).
  • Reject candidate when folder name and id mismatch.
  • Require deterministic metadata with interface_version: edge-finder-candidate/v1.
  • Use --dry-run in pipeline before full execution.

Resources

skills/edge-candidate-agent/scripts/export_candidate.py

Generate strategies/<candidate_id>/strategy.yaml and metadata.json from a research ticket YAML.

skills/edge-candidate-agent/scripts/validate_candidate.py

Run interface checks and optional StrategySpec/validate_spec checks against trade-strategy-pipeline.

skills/edge-candidate-agent/scripts/auto_detect_candidates.py

Auto-detect edge ideas from EOD OHLCV, generate exportable/research tickets, and optionally export/validate automatically.

references/pipeline_if_v1.md

Condensed integration contract for edge-finder-candidate/v1.

references/signal_mapping.md

Map hypothesis families to currently exportable signal families.

references/research_ticket_schema.md

Ticket schema used by export_candidate.py.

references/ideation_loop.md

Hint schema and external LLM ideation command contract.

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

Plan and assess backtests, which test trading rules against historical data. Examine sensitivity to rule changes, trading costs, and data bias, then use supplied performance metrics to generate a structured evaluation with reasons that block adoption.

中文简介正在准备中。当前显示英语简介。

  • Define a backtesting plan for rule-based trading
  • Test sensitivity to parameters and trading costs
  • Investigate suspiciously strong backtest results
tradermonty/claude-trading-skills32432026年10月21日 更新

Assess how broadly US stock market gains are shared across stocks using public CSV data and optional charts. Produce English reports covering market conditions, trading signals, scenarios, and positioning for different investment timeframes.

中文简介正在准备中。当前显示英语简介。

  • Checking how broadly US stocks are participating in a market rise
  • Reviewing medium- to long-term market positioning
  • Assessing short-term swing trading signals
tradermonty/claude-trading-skills32432026年10月21日 更新

Analyze chart images showing how broadly US stocks are participating in market trends. Assess medium-term conditions and short-term signals, then produce an English report with positioning guidance, alternative scenarios, and risks based on the visible data.

中文简介正在准备中。当前显示英语简介。

  • Assessing the market cycle from an S&P 500 breadth chart
  • Checking short-term signals in an uptrend stock ratio chart
  • Comparing medium-term and short-term market signals
tradermonty/claude-trading-skills32432026年10月21日 更新

Turn VCP screening results, which identify narrowing price swings, into breakout trade plans. Calculate entry, stop-loss, target prices, and position sizes using worst-case entries, while applying portfolio risk limits and producing Alpaca-compatible order templates.

中文简介正在准备中。当前显示英语简介。

  • Planning entries, stop-losses, and profit targets for VCP candidates
  • Calculating position sizes from account size and risk limits
  • Checking total portfolio risk and sector exposure
tradermonty/claude-trading-skills32432026年10月21日 更新

Screen US growth stocks with William O'Neil's CANSLIM method, which evaluates seven factors including earnings, price strength, trading volume, and market direction. Receive ranked candidates with composite scores, factor breakdowns, market warnings, and data quality notes.

中文简介正在准备中。当前显示英语简介。

  • Find US stocks with earnings growth and price momentum
  • Compare a chosen list of stocks using CANSLIM scores
  • Screen a sector-focused stock list
tradermonty/claude-trading-skills32432026年10月21日 更新

Combine three reports on crowded positions, failed reactions to news, and weekly price reversals into one trading setup status. Identify missing or invalid evidence and determine whether the setup is ready for planning.

中文简介正在准备中。当前显示英语简介。

  • Combine three contrarian strategy reports
  • Check which confirmations are still missing
  • Find stale or inconsistent input reports
tradermonty/claude-trading-skills32432026年10月21日 更新

查看 tradermonty 的全部技能

报告此技能的问题