agentsclimarketplace

Injective trading market data

Skill ChiJian28/Touchline/.agents/skills/injective-trading-market-data

World Cup sideline AI agent on Injective — CCTP, x402, MCP, Agent Skills, and binary options in one workflow.

Install
npx -y skills add ChiJian28/Touchline --skill injective-trading-market-data

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • 23 days oldThe repository was created 23 days ago. New is not bad, but a brand new repository carrying a familiar-sounding name is the shape a typosquat arrives in, and there has been no time for anyone else to find a problem with it.
  • 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Access real-time market data for Injective perpetual futures markets. Query oracle prices, list all active markets with metadata (tick size, min notional, max leverage), and retrieve current spread and funding information. Requires the Injective MCP server to be connected.

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

2.9 KB, 636 tokens by cl100k_base, as published. Nobody here has run it

Injective Trading Market Data, Skill Guide

Query live market data from Injective's on-chain perpetuals exchange. All data is pulled from the Injective Indexer (gRPC) and is real-time.

When to apply

Sample prompts: ./references/sample-prompts.md

Important

Notes

  • Prices are in USDT with 6 decimal places internally; returned as human-readable floats.
  • Oracle prices are aggregated from Band Protocol and Pyth Network feeds.
  • Funding rates are not yet exposed via MCP tools - check Helix UI for funding.
  • Market data is cached in-process for 30 seconds to reduce latency on repeated calls.
  • minPriceTickSize from the indexer is in chain format. For USDT markets, divide by 10^6 to get the human-readable tick size. minQuantityTickSize is already in human format (not scaled by quote decimals).

Market symbols

See: ./references/market-symbols.md

Use market_list for the complete current set, as new markets are added through Injective governance.

Activities

List all active perpetual futures markets with full metadata

market_list

Returns per market:

  • symbol - e.g. BTC, ETH, INJ
  • marketId - 0x... hex ID used on-chain
  • oraclePrice - current oracle mark price (USDT)
  • minQuantityTickSize - minimum order size
  • minPriceTickSize - minimum price increment
  • initialMarginRatio - minimum margin (1/maxLeverage)
  • maintenanceMarginRatio
  • makerFeeRate / takerFeeRate

Get the current oracle price for a single market.

market_price
  symbol: BTC    ← or ETH, INJ, SOL, ATOM, etc.

Returns: { symbol, price, marketId }

"What markets are available?"

market_list → filter/display by symbol

"What's the current BTC price?"

market_price BTC

"What's the max leverage for ETH?"

market_list → find ETH → compute 1 / initialMarginRatio

(e.g. initialMarginRatio 0.05 → 20x max leverage)

"Is the ETH market liquid enough for a $10,000 position?"

market_list → check ETH minQuantityTickSize and current oracle price

Injective uses an on-chain order book. For large orders, use limit orders or split into multiple market orders to reduce slippage.

Related skills

  • injective-mcp-servers

If these skills are not available, selectively run the following commands to install them:

npx skills add InjectiveLabs/agent-skills --skill injective-mcp-servers

Prerequisites

  • Injective MCP server must be running
  • User prompts should be issued from an AI tool that is configured to talk to the Injective MCP server

Gives 0 of the 12 instructions most mcp tooling skills give in 636 tokens

Counted across 638 of the 750 authors here whose files we hold, read 2026-08-07

  • create ten complex read-only evaluation questionsin 69 of 638, across 15 files
  • test servers using MCP Inspectorin 61 of 638, across 19 files
  • provide actionable error messagesin 54 of 638, across 12 files
  • prioritize comprehensive API coverage over specific workflowsin 54 of 638, across 12 files
  • use TypeScript and Streamable HTTP for remote serversin 54 of 638, across 8 files
  • define structured output schemas where possiblein 50 of 638, across 8 files
  • use Zod or Pydantic for input schemasin 47 of 638, across 5 files
  • fetch MCP specification pages with markdown suffixin 46 of 638, across 4 files
  • load framework documentation using WebFetchin 45 of 638, across 3 files
  • verify each evaluation answer independentlyin 45 of 638, across 3 files
  • implement API client with authentication and paginationin 45 of 638, across 3 files
  • Define input schemas with validationin 27 of 638, across 9 files

Said here and by no other author read

  • use market_list for current market symbols
  • use market_price to get a single market price
  • compute max leverage as one divided by initial margin ratio
  • divide minPriceTickSize by 1000000 for USDT markets
  • do not scale minQuantityTickSize by quote decimals
  • check the Helix UI for funding rates

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.