Claude Trading Skills is a collection of Claude Code workflows for individual investors who want structured market analysis, charting, economic-calendar review, screening, trade planning, journaling, and risk management. It is designed for people using long-term investing, ETFs, dividend stocks, and disciplined swing trading, and the catalogue entries package these workflows as skills, agents, commands, settings, and instructions.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add tradermonty/claude-trading-skills --skill edge-candidate-agentgit clone --depth 1 https://github.com/tradermonty/claude-trading-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/tradermonty/claude-trading-skills/edge-candidate-agent)<a href="https://agentmods.dev/skills/tradermonty/claude-trading-skills/edge-candidate-agent"><img src="https://agentmods.dev/badge/skills/tradermonty/claude-trading-skills/edge-candidate-agent/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/tradermonty/claude-trading-skills/edge-candidate-agent"><img src="https://agentmods.dev/badge/skills/tradermonty/claude-trading-skills/edge-candidate-agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket warn
- Snyk warn
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00085 | $0.01314 |
| Opus 5.5 | $0.00034 | $0.00526 |
| Sonnet 5.5 | $0.00017 | $0.00263 |
| Haiku 4.5 | $0.00009 | $0.00131 |
Grade A, and why
edge-candidate-agent scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
2 near-identical copies found in the catalogue:
- edge-candidate-agent — 100% identical, 0 lines differ
- edge-candidate-agent — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.jsonfortrade-strategy-pipelinePhase I. - Run preflight compatibility checks for
edge-finder-candidate/v1before pipeline execution.
Prerequisites
- Python 3.9+ with
PyYAMLinstalled. - Access to the target
trade-strategy-pipelinerepository for schema/stage validation. uvavailable 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.mdmarket_summary.jsonanomalies.jsonwatchlist.csvtickets/exportable/*.yamltickets/research_only/*.yaml
Position in Split Workflow
Recommended split workflow:
skills/edge-hint-extractor: observations/news ->hints.yamlskills/edge-concept-synthesizer: tickets/hints ->edge_concepts.yamlskills/edge-strategy-designer: concepts ->strategy_drafts+ exportable ticket YAMLskills/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:
--hintsfor human ideation input - Optional:
--llm-ideas-cmdfor external LLM ideation loop
- Load the contract and mapping references:
references/pipeline_if_v1.mdreferences/signal_mapping.mdreferences/research_ticket_schema.mdreferences/ideation_loop.md
- Build or update a research ticket using
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-pipelineand run dry-run first.
What ships with it
20 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 282 B
- references/ideation_loop.md 1.3 KB
- references/pipeline_if_v1.md 1.6 KB
- references/research_ticket_schema.md 1.2 KB
- references/signal_mapping.md 1.2 KB
- requirements.txt 238 B
- scripts/auto_detect_candidates.py 68 KB runs code
- scripts/candidate_contract.py 7.8 KB runs code
- scripts/export_candidate.py 11 KB runs code
- scripts/tests/conftest.py 148 B runs code
- scripts/tests/synthetic_ohlcv.py 4.3 KB runs code
- scripts/tests/test_auto_detect_candidates.py 8.4 KB runs code
- scripts/tests/test_auto_detect_dataframes.py 25 KB runs code
- scripts/tests/test_auto_detect_main.py 16 KB runs code
- scripts/tests/test_auto_detect_units.py 14 KB runs code
- scripts/tests/test_candidate_contract.py 7.0 KB runs code
- scripts/tests/test_contract_export_validate_edges.py 14 KB runs code
- scripts/tests/test_export_candidate.py 7.5 KB runs code
- scripts/tests/test_validate_candidate.py 7.4 KB runs code
- scripts/validate_candidate.py 4.9 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 141 lines · 85 tokens per session scan A 6c9545ce9662
edge-candidate-agent is a skill published in the GitHub repository tradermonty/claude-trading-skills (3,373 stars, last pushed yesterday), licensed MIT. It adds 85 tokens to every session and 1,314 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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