What is crypto-trade-context?

A guide for understanding the data around a cryptocurrency trade, including crowding, funding costs, whale activity and forced selling. It helps describe market conditions without deciding whether to buy or sell.

Use it to assess a coin before entering or exiting, check whether traders are crowded on one side, estimate holding costs and monitor whale flow or liquidations.

It brings several relevant signals together so you do not have to piece them together while entering or holding a position.

crypto-trade-context — Skill for Claude Code by CoinLobster

Install

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.

Any agent

npx skills add CoinLobster/agent-skills --skill crypto-trade-context

Clone the repo

git clone --depth 1 https://github.com/CoinLobster/agent-skills

Made for: Claude Code.

Or install coinlobster, the plugin that ships this one along with the rest of its 6 skills, 1 MCP server.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/coinlobster/agent-skills/crypto-trade-context/github.svg)](https://agentmods.dev/skills/coinlobster/agent-skills/crypto-trade-context)

Your own site

<a href="https://agentmods.dev/skills/coinlobster/agent-skills/crypto-trade-context"><img src="https://agentmods.dev/badge/skills/coinlobster/agent-skills/crypto-trade-context/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/coinlobster/agent-skills/crypto-trade-context"><img src="https://agentmods.dev/badge/skills/coinlobster/agent-skills/crypto-trade-context.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 205 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,116 The whole file, excluding the scripts and references it only reads on demand.

Security scan B 2 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00205	$0.02116
Opus 5	$0.00102	$0.01058
Sonnet 5	$0.00041	$0.00423
Haiku 4.5	$0.00020	$0.00212

Measured 11d ago against content hash c847987979cb, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade B, and why

crypto-trade-context scanned grade B with 2 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 11d 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.

Sends data to an external URLmediumData exfiltration

A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.

> curl -s -X POST https://coinlobster.com/mcp -H 'Content-Type: application/json' -H 'Accept: application/json, text/event-stream' -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"market_snapshot","arg

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

description: "The data picture around a crypto position. Use when the user is about to enter or exit, is holding a position and wants what to watch, asks if their side is crowded, what holding costs, whether whales are o

skills/crypto-trade-context/SKILL.md · 67 lines

How it starts

The opening of the file, as written. The whole thing — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Crypto Trade Context

The user is making or holding a trade. Your job is the data picture, stated so they can decide: crowding as a percentile of the coin's own recorded days, carry cost in dollars, whale direction vs their side, where forced selling actually fired, and what to watch while holding. The decision is theirs; you never make it.

Data sources (in order)

MCP connected? coinlobster:trade_context (args: pair, optional position_usd, optional compact) is the one-call blob: price, 24h stats, funding + OI with percentile judgment vs the pair's own recorded days, whale flow vs the coin's own baseline, visible liquidations, carry arithmetic, crowding (keyed). Keyless it answers on EVERY streamed pair; depth reports which shape you got (lite off the free pair, free-pair, or keyed) and locked_layers names exactly what a developer plan key (from $29/mo) adds: stats_24h, whale_flow USD magnitudes and crowding. vs_own_history is never locked: the percentile judgment is keyless on every pair, here and on /api/public/baseline and market_screener.

No MCP: assemble the same picture keyless:

curl -s "https://coinlobster.com/api/public/baseline?pair=BTC/USD"        # percentile judgment + outcome history
curl -s "https://coinlobster.com/api/public/whale-context?coin=BTC"       # whale flow vs own baseline (coin param required)
curl -s "https://coinlobster.com/api/public/liquidation-history?pair=BTC/USD&limit=100"  # history[]: quantity_quote, isBuy (false = a long was force-sold)

Companion MCP tools when present: funding_matrix (per-venue rates, keyless on any streamed pair), squeeze_score (developer plan only: keyless it answers available: false), liq_zones (projected levels, labeled as a projection; keyless it covers the free pair only and drops the cascade chains).

On ANY non-200 (401/400/404 alike), fall back and keep a vs-own-history layer in the answer: /api/public/whale-context?coin=X carries the whale multiple, the buy-share baselines AND the USD behind them keyless (ctx.usd24, ctx.net24, ctx.avgDayUsd), which the whale_context MCP tool withholds without a key. When the tool locks magnitudes, this endpoint is where you get them. The last 24h of /api/public/crypto-whales rows embed per-trade funding/OI (marketConditions) for a crude funding-range check. Without an MCP client, every tool answers a raw POST:
curl -s -X POST https://coinlobster.com/mcp -H 'Content-Type: application/json' -H 'Accept: application/json, text/event-stream' -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"market_snapshot","arguments":{"pair":"BTC/USD"}}}'

Read the full file on GitHub · 67 lines

Changes

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.

11d ago First seen · 67 lines · 205 tokens per session scan B c847987979cb

Subscribe to this mod's changes

crypto-trade-context is a skill published in the GitHub repository CoinLobster/agent-skills (9 stars, last pushed 28d ago), licensed MIT. It adds 205 tokens to every session and 2,116 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Finance and fintech Web3 and blockchain agent-skills ai-agent ai-agents chatgpt-skills claude-skills crypto

crypto-token-analysis

Deep-dive framework for analyzing crypto tokens — market data, liquidity health, tokenomics, unlock schedules, and risk assessment. Combines on-chain data, API queries, and multi-source validation to generate actionable investment verdicts.

kevinnft/ai-agent-skills · 49 tokens

crypto-defi-trading

Crypto and DeFi trading: DEX analysis (Uniswap, SushiSwap, Curve), on-chain analytics, MEV detection, impermanent loss, yield farming metrics, DeFi risk analysis, token metrics, liquidity pool analysis, whale tracking, exchange netflow. USE FOR: crypto, defi, dex, uniswap, sushiswap, curve, impermanent loss, yield…

mahmoud20138/Tradecraft · 107 tokens

freqtrade-bot

Freqtrade — open-source Python crypto trading bot. Backtesting, hyperopt (ML parameter optimization), FreqAI (self-training adaptive strategies), Telegram + WebUI control. Supports Binance, Kraken, Bybit, OKX, Gate.io (spot + futures). SQLite trade h.

mahmoud20138/Tradecraft · 61 tokens

trading-signals

Fetches live AI crypto trading signals with entry price, stop-loss, take-profit, leverage, confidence scores, and automated verification. Covers 50+ coins including BTC, ETH, SOL. Use when the user asks for crypto signals, trade ideas, market direction, portfolio analysis, or wants to build a trading bot.

roman-rr/trading-skills · 69 tokens

crypto-derivatives

Crypto-derivatives strategies — perpetual funding-rate arbitrage, futures term-structure contango/backwardation trading, and option volatility-smile / Greeks analysis.

HKUDS/Vibe-Trading · 37 tokens

defi-yield

DeFi yield analysis and optimization — lending rates, LP yields, staking returns, yield farming strategies, risk-adjusted yield comparison, and protocol-level sustainability assessment.