edge-candidate-agent

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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.

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Sourcetradermonty/claude-trading-skills

Added on2026-02-24

NPX Install

npx skill4agent add tradermonty/claude-trading-skills edge-candidate-agent

SKILL.md Content

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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:

```
skills/edge-hint-extractor
```
: observations/news ->
```
hints.yaml
```

skills/edge-concept-synthesizer

: tickets/hints ->

edge_concepts.yaml

skills/edge-strategy-designer

: concepts ->

strategy_drafts

+ exportable ticket YAML

```
skills/edge-candidate-agent
```
(this skill): export + validate for pipeline handoff

Workflow

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

Load the contract and mapping references:

skills/edge-candidate-agent/references/pipeline_if_v1.md

skills/edge-candidate-agent/references/signal_mapping.md

skills/edge-candidate-agent/references/research_ticket_schema.md

skills/edge-candidate-agent/references/ideation_loop.md

Build or update a research ticket using

skills/edge-candidate-agent/references/research_ticket_schema.md

.

Export candidate artifacts with

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

.

Validate interface and Phase I constraints with

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

.

Hand off candidate directory to
```
trade-strategy-pipeline
```
and run dry-run first.

Quick Commands

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

bash

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:

bash

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:

bash

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:

bash

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.

skills/edge-candidate-agent/references/pipeline_if_v1.md

Condensed integration contract for

edge-finder-candidate/v1

.

skills/edge-candidate-agent/references/signal_mapping.md

Map hypothesis families to currently exportable signal families.

skills/edge-candidate-agent/references/research_ticket_schema.md

Ticket schema used by

export_candidate.py

.

skills/edge-candidate-agent/references/ideation_loop.md

Hint schema and external LLM ideation command contract.

edge-candidate-agent

NPX Install

Tags

SKILL.md Content

Edge Candidate Agent

Overview

When to Use

Prerequisites

Output

Position in Split Workflow

Workflow

Quick Commands

Export Rules

Guardrails

Resources

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

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

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

`skills/edge-candidate-agent/references/pipeline_if_v1.md`

`skills/edge-candidate-agent/references/signal_mapping.md`

`skills/edge-candidate-agent/references/research_ticket_schema.md`

`skills/edge-candidate-agent/references/ideation_loop.md`