event-driven-market-neutral-trader

name	event-driven-market-neutral-trader
description	Use for implementation, review, or documentation work in the event-driven-market-neutral-trader repo, especially core trading models, prediction-market orderbook normalization, risk policy, and demo-first execution safety.

Event Driven Market Neutral Trader

When to use

Use this Skill for changes in this repository that affect project scaffolding, trading-domain models, adapters, risk policy, simulations, execution workflow, tests, or public-facing documentation.

Desired outcome

Produce small, reviewable changes that support a demo-first, risk-controlled trading research platform for event-driven prediction markets without enabling production trading.

Success criteria

• No profitability guarantees or claims.
• No credentials, private keys, API keys, tokens, or secrets.
• No authenticated API calls or live order placement unless explicitly requested in a later reviewed stage.
• Exchange-specific logic stays under src/edmn_trader/adapters.
• Core models stay exchange-agnostic.
• Prices, quantities, cash, fees, and PnL use Decimal.
• Functional changes include deterministic tests.
• pytest and ruff check . pass before handoff when the local environment supports them.

Inputs and context to collect

• Read AGENTS.md first.
• Identify the requested stage and stop at the requested boundary.
• Check existing package layout and tests before adding new abstractions.
• Confirm whether the task permits live API use; default to local fixtures only.

Workflow guidance

Start with the safety boundary, then implement the narrowest foundation needed for the requested stage. Keep adapters thin and explicit, normalize exchange-specific inputs into canonical core objects, and prefer deterministic fixtures over external services.

Use docs/codex_long_running_controller.md for long-session governance, token-budget discipline, publish rules, and optional skill orchestration. Treat this project Skill as the required repository-specific skill for staged work; use optional Matt Pocock, TDD, Ponytail, and handoff/compaction skills only in the cases named by the controller, and fall back to the equivalent checklist if an optional skill is unavailable or renamed.

In continuous autopilot, compact governance audits after every three completed checkpoints are mandatory but non-terminal when they pass. After a passing audit is folded into the active delivery branch or otherwise published, wait for main Validate, sync local main, verify a clean state, read the updated handoff, reset the checkpoint counter, and continue.

Use delivery-unit batching for staged work: keep readiness clarification, implementation, tests, docs/log/changelog updates, handoff updates, and due passing audit notes on one codex/ branch when they form one coherent delivery unit. Do not publish every small docs or handoff edit; publish after the unit is complete, validated, risk-classified, and reviewed. Use docs-only PRs or stop only for high/unclear risk, compliance ambiguity, external credentials, production endpoints, broker integration, live data, strategy advice, or user judgment.

Use optional skills only when they save tokens or reduce risk. Use TDD for behavior changes, Ponytail review before final publish for implementation diffs, Matt Pocock grill-with-docs only for ambiguous/high-risk design or domain terminology drift, EDD/eval-before-ship style only when installed and useful or by equivalent checklist, and Skill Maker / skill-creator only after a workflow repeats at least twice. If an optional skill is unavailable, renamed, or noisy to invoke, use the equivalent checklist and continue.

For Kalshi-style binary orderbooks, normalize YES-side books from local data by treating YES bids as canonical bids and NO bids as implied YES asks using 1 - no_price.

For current roadmap work, prioritize same-market YES/NO complement parity research over additional report-input metadata kinds. The active roadmap is docs/ARBITRAGE_ROADMAP.md; the first offline candidate model lives under src/edmn_trader/arb/ and must remain Decimal-only, deterministic, and non-executable until later reviewed stages add fee models, scanners, recorders, simulation, or execution gates.

For staged project work, read docs/current_handoff.md and docs/repo_map.md before broad exploration. After a stage-sized change, update docs/current_handoff.md, docs/engineering_log.md, and CHANGELOG.md with concise durable context.

Known pitfalls

• Kalshi-style binary orderbooks expose YES bids and NO bids, not traditional YES asks.
• A V2 side value of bid means buy YES, while ask means sell YES.
• Stage 0 and the first Stage 1 slice must not place orders, open WebSockets, or call live APIs in tests.

Tools and deterministic operations

• Install locally for validation: python -m pip install -e ".[dev]".
• Run tests: pytest.
• Run lint: ruff check ..
• Use local JSON fixtures for orderbook normalization tests and replay scripts.
• The Stage 1 fixture replay path is scripts/01_replay_orderbook_fixture.py, backed by tests/fixtures/kalshi_orderbook_fp_basic.json and the importable entry point edmn_trader.scripts.replay_orderbook_fixture:main.
• The Stage 2 read-only client lives at src/edmn_trader/adapters/kalshi/client.py; tests use httpx.MockTransport in tests/test_kalshi_client.py and local fixtures under tests/fixtures/.
• The Stage 3 offline data layer lives under src/edmn_trader/data/; scripts are scripts/02_record_fixture_snapshots.py and scripts/03_replay_snapshots.py. Replay is strict by default and sorts only when --no-strict is explicitly requested.
• The Stage 4 dry-run quote layer lives under src/edmn_trader/research/; scripts/04_quote_replay_dry_run.py must remain local/replay-only and must emit non-executable dry_run_only quote intents.
• The Stage 5 execution smoke layer lives under src/edmn_trader/execution/; scripts/05_demo_execution_smoke.py must remain fake-adapter/local by default, require explicit --demo-opt-in for approved fake execution, and log every attempt as JSONL.
• The Stage 6 finite market-maker replay lives at src/edmn_trader/scripts/market_maker_replay.py; the root script is scripts/06_market_maker_replay.py. It must remain finite, dry-run by default, fake-adapter only after explicit --demo-opt-in, and must not infer fills, PnL, profitability, or production readiness.
• The Stage 7 offline research report lives at src/edmn_trader/scripts/research_report.py; the root script is scripts/07_research_report.py. It consumes Stage 6 logs and optional explicit local fill fixtures only, rejects secret-like fill fields, and must not infer fills from adapter submissions or claim profitability.
• The Stage 8 Polymarket US adapter lives under src/edmn_trader/adapters/polymarket_us/. It must stay public-market-data only, fixture-tested by default, restricted to the Polymarket US public base URL, and free of international endpoints, auth, wallets, WebSockets, trading, execution paths, and profitability claims.

Verification

Check that the requested stage boundary was not exceeded, tests cover normal and edge cases, and docs clearly describe demo-first scope, risk controls, live-trading restrictions, and extension plans.

For the Stage 0 and Stage 1 foundation, the verified local command set is: python -m pip install -e ".[dev]", pytest, ruff check ., and python scripts/01_replay_orderbook_fixture.py.

Update policy

After each use, update this Skill only with reusable lessons verified in that run. Keep updates concise and specific to this repository.