What does this skill do, and when should you use it?
Lighter Agent Kit packages the full trading surface of the Lighter DEX into three Python scripts for AI agents: query.py for market data and account reads, trade.py for signed writes (orders, cancels, leverage, withdrawals), and paper.py for local simulation against live order-book snapshots. It works identically across Lighter mainnet/testnet and the Robinhood Chain deployments, with every command following `<group> <action>` syntax and emitting structured JSON. Public market reads need no credentials; account-private reads and writes require a Lighter API key. It suits crypto and quant traders who already have a Lighter account and want to manage positions through natural language in agents like Claude Code.
Reads order books, recent fills, OHLCV candles (1m–1d), funding rates, market metadata, and account balances/positions; executes limit and market orders (with reduce_only, post_only, a default 1% slippage budget), order modification, single cancels, cancel_all, close_all position flattening, leverage and isolated-margin changes, unified-margin mode and per-asset collateral toggles, plus self-directed perp/spot bucket transfers and withdrawals. Writes auto-scale human-unit prices/amounts to integer ticks/lots and echo effective_amount/effective_price. paper.py simulates market and IOC orders against real book snapshots locally — perps only, no credentials, no broadcast.
- A crypto trader asking an agent in plain language which perp has the tighter spread, BTC or ETH, then placing an order without leaving the chat
- A quant validating a momentum strategy risk-free on paper.py against live order-book snapshots before going live
- A portfolio monitor pulling portfolio performance and funding rates on a schedule, flagging rates above an annualized threshold
- A user active on both Lighter and Robinhood Lighter operating both deployments with identical commands via LIGHTER_HOST
- A trader cleaning up an account in bulk with cancel_all or a previewed close_all
How do you install this skill?
- The skill executes real, irreversible crypto orders/withdrawals/transfers — validate on testnet or paper.py first and never auto-grant funded API keys without explicit approval.
- Core function depends on pypi.org, github.com and overseas Lighter hosts; mainland-China network reachability is unaddressed, and claude.ai sandbox needs expanded egress allowlist.
- Account-wide operations (order close_all, account mode, account collateral) are extremely high risk; the non-preview forms must receive per-call explicit user confirmation.
- Publisher is unverified by the FollowSkills registry and dependencies install from PyPI/GitHub at first run — audit requirements.lock and the pinned lighter-sdk before live funds.
- Shell / CLI
- Network access
- Local filesystem
Python 3.9+lighter-sdk (auto-vendored, pinned by requirements.lock)
One-line install: curl -fsSL https://github.com/elliottech/lighter-agent-kit/releases/latest/download/install.sh | bash — it detects your platform (macOS arm64, Linux x86_64/arm64), installs Python if needed, and registers the skill with your chosen agents; restart your agent session. Manual: git clone https://github.com/elliottech/lighter-agent-kit ~/.agents/skills/lighter-agent-kit, then symlink for Claude Code at ~/.claude/skills/lighter-agent-kit/ (or project-scoped under .claude/skills/). lighter-sdk auto-vendors on first call. For writes, generate a key at app.lighter.xyz/apikeys and run ./lighter-config to write ~/.lighter/lighter-agent-kit/credentials, or export LIGHTER_API_PRIVATE_KEY / LIGHTER_ACCOUNT_INDEX / LIGHTER_API_KEY_INDEX.
git clone --depth 1 https://github.com/elliottech/lighter-agent-kit.git ~/.claude/skills/lighter-agent-kitGenerated from the source repository and skill path; it copies only this skill's folder. If the author's install steps above differ, follow those first. To scope it to one project, replace ~/.claude/skills with that project's .claude/skills.
How do you use this skill?
Once installed, send your agent any of these to trigger it:
- List current funding rates and flag anything above 10% annualized
- Place a limit buy for 0.01 ETH at $50 under the current mid.
Trigger with natural language, e.g. "List current funding rates and flag anything above 10% annualized" or "Place a limit buy for 0.01 ETH at $50 under the current mid." Or run scripts directly: python3 scripts/query.py market book BTC --limit 10, python3 scripts/trade.py order limit BTC --side long --amount 0.01 --price 60000, python3 scripts/paper.py init && python3 scripts/paper.py order market BTC --side long --amount 0.1. Symbols: bare tickers for perps (BTC), /-separated pairs for spot (ETH/USDC) — no --market_type needed. High-impact commands (close_all, account mode, account collateral) require --preview / account inspection and explicit user approval first.
What are this skill's strengths and limitations?
- Comprehensive coverage: market data, orders, leverage, margin, transfers, and withdrawals in one skill; public reads are fully credential-free
- paper.py simulates against real order-book snapshots with no keys and no broadcast, enabling risk-free strategy rehearsal
- All output is structured JSON with a uniform {"error": ...} envelope — easy for agents and scripts to parse
- One environment variable switches between Lighter/Robinhood Lighter and mainnet/testnet
- Dependencies pinned by requirements.lock and vendored inside the skill folder; uninstall is just removing the .vendor directory
- No Intel Mac support (darwin-x86_64); platforms limited to macOS arm64 and Linux x86_64/arm64
- claude.ai's sandbox has no persistent shell for env vars, making account-private reads effectively unusable there; its default egress allowlist also excludes github.com
- Paper mode has real structural limits: no maker fills, no book impact, no funding accrual, cross-margin only, perps only, market/IOC only — paper and live PnL will diverge
- Sub-account routing, cross-account transfers, and API key rotation are deliberately unsupported (rotation needs an ETH private key and is high-risk)
- Withdrawals are not instant wallet credits — they pass through Lighter's pending/claim flow; no test suite is mentioned in the source
How does this skill compare with similar options?
Side by side with related skills; every score comes from the same FSRS standard.
| Skill | FS score | Stars | Last updated | License |
|---|---|---|---|---|
| Lighter Agent Kit this page | 57 · Use with care | ★ 67 | 2mo ago | MIT |
| Minara — Personal Crypto AI CFO | 51 · Use with care | ★ 362 | 1mo ago | — |
| Pro Bias Analyst | 44 · Not recommended | ★ 2.1k | 2mo ago | AGPL-3.0 |
| Bybit AI Trading Skill | 51 · Use with care | ★ 83 | 12d ago | MIT |
| Polymarket Public Data Skill | 50 · Use with care | ★ 23k | 4mo ago | — |
How did FollowSkills review this skill?
SKILL.md clearly separates reads/writes, forbids echoing credentials, marks close_all/account mode/withdraw as high-risk requiring explicit user approval, refuses cross-account transfers and key rotation, and provides paper.py risk-free simulation plus rollback notes (rm -rf .vendor). Deductions: writes sign and broadcast immediately and are irreversible; least privilege relies on the host agent's tool approval rather than in-skill enforcement; first call pulls pinned lighter-sdk from PyPI/GitHub, so supply-chain trust rests on pinning rather than auditable code.
Docs are self-consistent: uniform JSON error envelope, --help everywhere, bootstrap diagnostic, health.py self-check, and committed offline tests covering paper state serialization/corruption recovery, symbol cache, and trade orchestration with specific error messages. Deductions: static review executed nothing, no CI workflow in evidence, live write-path failure feedback against the real API is inferable only from docs.
Triggers are explicit (Lighter/zkLighter/perps/positions/PnL), with clear platform support, claude.ai sandbox limits, symbol conventions, and non-fit boundaries. Deductions: core function depends entirely on overseas services (pypi.org, github.com, Lighter hosts) with no mainland-China reachability notes or fallbacks.
Well-layered docs: concise SKILL.md, references/ for schemas, README with install and command index, MIT license, release-based versioning, disclaimer. Deductions: no CHANGELOG, maintenance responsibility and update path only implicit, publisher unverified, references/ contents not provided in this review.
Clear goal (AI agents querying and trading on Lighter), human-unit parameters, precision echoback, swappable paper/live engines support real marginal value. Deductions: static review cannot verify outputs are directly usable, and comparative-benefit evidence is limited.
Repo includes offline tests for key paths (paper accounting, state recovery, symbol cache, trade orchestration) and reproducible sanity-check commands. Deductions: no CI evidence in files, tests not executed, no third-party corroboration; claims beyond static audit (platform support, install timing) unverifiable.
Open a dimension to read why it scored that way
Evidence confidence：Low — Mostly static review, author material or a limited demo; useful for discovery, not high-risk decisions.
See the full review method →