Edge Pipeline Orchestrator Skill for Claude
Orchestrate the full edge research pipeline from candidate detection through strategy design, review, revision, and export. Use when coordinating multi-stage edge research workflows end-to-end.
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/BaggaT236/AI-Trading-Skills --skill edge-pipeline-orchestratorWhat comes with it
108 919 bytes besides the instructionThe instruction itself
8 sections, as written by the authorEdge Pipeline Orchestrator
Coordinate all edge research stages into a single automated pipeline run.
When to Use
- Run the full edge pipeline from tickets (or OHLCV) to exported strategies
- Resume a partially completed pipeline from the drafts stage
- Review and revise existing strategy drafts with feedback loop
- Dry-run the pipeline to preview results without exporting
Workflow
- Load pipeline configuration from CLI arguments
- Run auto_detect stage if --from-ohlcv is provided (generates tickets from raw OHLCV data)
- Run hints stage to extract edge hints from market summary and anomalies
- Run concepts stage to synthesize abstract edge concepts from tickets and hints
- Run drafts stage to design strategy drafts from concepts
- Run review-revision feedback loop:
- Review all drafts (max 2 iterations)
- PASS verdicts accumulated; REJECT verdicts accumulated
- REVISE verdicts trigger apply_revisions and re-review
- Remaining REVISE after max iterations downgraded to research_probe
- Export eligible drafts (PASS + export_ready_v1 + exportable entry_family)
- Write pipeline_run_manifest.json with full execution trace
CLI Usage
# Full pipeline from tickets
python3 scripts/orchestrate_edge_pipeline.py \
--tickets-dir path/to/tickets/ \
--output-dir reports/edge_pipeline/
# Full pipeline from OHLCV
python3 scripts/orchestrate_edge_pipeline.py \
--from-ohlcv path/to/ohlcv.csv \
--output-dir reports/edge_pipeline/
# Resume from drafts stage
python3 scripts/orchestrate_edge_pipeline.py \
--resume-from drafts \
--drafts-dir path/to/drafts/ \
--output-dir reports/edge_pipeline/
# Review-only mode
python3 scripts/orchestrate_edge_pipeline.py \
--review-only \
--drafts-dir path/to/drafts/ \
--output-dir reports/edge_pipeline/
# Dry run (no export)
python3 scripts/orchestrate_edge_pipeline.py \
--tickets-dir path/to/tickets/ \
--output-dir reports/edge_pipeline/ \
--dry-run
Output
All artifacts are written to --output-dir:
output-dir/
├── pipeline_run_manifest.json
├── tickets/ (from auto_detect)
├── hints/hints.yaml (from hints)
├── concepts/edge_concepts.yaml
├── drafts/*.yaml
├── exportable_tickets/*.yaml
├── reviews_iter_0/*.yaml
├── reviews_iter_1/*.yaml (if needed)
└── strategies/<candidate_id>/
├── strategy.yaml
└── metadata.json
Claude Code LLM-Augmented Workflow
Run the LLM-augmented pipeline entirely within Claude Code:
- Run auto_detect to produce
market_summary.json+anomalies.json - Claude Code analyzes data and generates edge hints
- Save hints to a YAML file:
- title: Sector rotation into industrials
observation: Tech underperforming while industrials show relative strength
symbols: [CAT, DE, GE]
regime_bias: Neutral
mechanism_tag: flow
preferred_entry_family: pivot_breakout
hypothesis_type: sector_x_stock
- Run orchestrator with
--llm-ideas-fileand--promote-hints:
python3 scripts/orchestrate_edge_pipeline.py \
--tickets-dir path/to/tickets/ \
--llm-ideas-file llm_hints.yaml \
--promote-hints \
--as-of 2026-02-28 \
--max-synthetic-ratio 1.5 \
--strict-export \
--output-dir reports/edge_pipeline/
Optional Flags
--as-of YYYY-MM-DD— forwarded to hints stage for date filtering--strict-export— export-eligible drafts with any warn finding get REVISE instead of PASS--max-synthetic-ratio N— cap synthetic tickets to N × real ticket count (floor: 3)--overlap-threshold F— condition overlap threshold for concept deduplication (default: 0.75)--no-dedup— disable concept deduplication
Note: --llm-ideas-file and --promote-hints are effective only during full pipeline runs.
--resume-from drafts and --review-only skip hints/concepts stages, so these flags are ignored.
Resources
references/pipeline_flow.md— Pipeline stages, data contracts, and architecturereferences/revision_loop_rules.md— Review-revision feedback loop rules and heuristics
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How to use it
Take baggat236/edge-pipeline-orchestrator from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.