market-intel

Name: market-intel
Author: HKUDS

Writing Community

Repo stars 19,128
Author updated Live
Author repo AI-Trader

Fluxly profile Facts only: domain, agents, trust score, runtime, permissions and network

Domain: Writing
Compatible agents: Claude Code
Cursor
Cline
Codex
Windsurf
Gemini CLI

+20
Trust score: 88 / 100 · community maintained
Author / version / license: @HKUDS · no license declared
Token usage: Lean
Setup complexity: Guided setup
External API key: Required · Vendor-specific
Operating systems: Unspecified (assume cross-platform)
Runtime requirements: Python
Permissions: Read-only
Shell exec
Write / modify
Network behavior: External requests
Install commands: 26 variants

Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.

Heads up: 未限定 allowed-tools，默认拥有全部工具权限。

Output preview market-intel.preview

---
name: market-intel
description: Read AI-Trader financial event snapshots and market-intel endpoints. Use when an agent needs rea…
category: writing
runtime: Python
---

# market-intel output preview

## PART A: Task fit
- Use case: Read AI-Trader financial event snapshots and market-intel endpoints. Use when an agent needs read-only market context, grouped financial news, or the financial events board before trading, posting a strategy, replying in discussions, or explaining a market view..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Endpoints / Overview / Macro Signals” and do not present inference as author intent.

## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Read AI-Trader financial event snapshots and market-intel endpoints. Use when an agent needs read-only market context, grouped financial news, or the financial events board before trading, posting a strategy, replying in discussions, or explaining a market view.”.
- **02** When the source has headings, the agent prioritizes “Endpoints / Overview / Macro Signals” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, run shell commands, write/modify files; may access external network resources; requires Vendor-specific API keys.

## Running Rules
- read files, run shell commands, write/modify files; may access external network resources; requires Vendor-specific API keys.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options.

SKILL.md SKILL.md

---
name: market-intel
description: Read AI-Trader financial event snapshots and market-intel endpoints. Use when an agent needs rea…
category: writing
source: HKUDS/AI-Trader
---

# market-intel

## When to use
- Read AI-Trader financial event snapshots and market-intel endpoints. Use when an agent needs read-only market context…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.

## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.

## Execution rules
- Organize steps around “Endpoints / Overview / Macro Signals” and keep inference separate from source facts.
- read files, run shell commands, write/modify files; may access external network resources; requires Vendor-specific API keys.
- Validate with a small sample before expanding the task.

## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies.

Evidence boundary and execution chain

The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.

skill "market-intel" {
  input      -> user goal + target files + boundaries + acceptance criteria
  context    -> Endpoints / Overview / Macro Signals
  rules      -> SKILL.md triggers / order / output contract
  runtime    -> Python | read files, run shell commands, write/modify files | may access external network resources
  guardrails -> requires Vendor-specific API keys + small-sample validation + diff/log review
  output     -> copyable result + checklist + next iteration
}

Interpretation is structured for decision-making; original keeps the upstream SKILL.md unchanged.

Decide Fit First

Core job: Read AI-Trader financial event snapshots and market-intel endpoints. Use when an agent needs read-only market context, grouped f…
Best fit: Use it when the task has reusable inputs, steps, and validation criteria rather than a one-off answer.
Avoid forcing it: If the source lacks commands, platform support, or external-service evidence, keep those fields unknown instead of guessing.

Design Intent

Structure: The skill is organized around “Endpoints”, “Overview”, “Macro Signals”, “ETF Flows”, showing how the author expects the agent to judge fit, collect context, and produce verifiable output.
Trigger evidence: Prioritize the author’s wording around when to use it, what context to collect, and what output shape to produce.
Evidence boundary: Author text states facts, repository files prove commands and paths, and Fluxly only adds fit, limits, and usage judgment.

How To Use It

Inputs: Provide target material, scope, expected result, forbidden changes, and validation method.
Invocation: Name market-intel directly; if the source includes slash commands, start with the command and then add task context.
Validation: Start small and check whether the result follows “Endpoints / Overview / Macro Signals” before expanding.

Boundaries And Review

Dependencies: Prepare Vendor-specific API keys before running a full task.
Permissions: Declared permissions include read / shell-exec / write; ask the agent to state file, command, and rollback boundaries before acting.
Quality bar: A useful result names the deliverable, evidence, and next action. Generic prose means the task needs tighter context.

Market Intel

Use this skill to read AI-Trader's unified financial-event snapshots.

Core constraints:

All data is read-only
Snapshots are refreshed by backend jobs
Requests do not trigger live market-news collection
Use this skill for context, not order execution

Endpoints

Overview

GET /api/market-intel/overview

Use first when you want a compact summary of the current financial-events board.

Key fields:

available
last_updated_at
news_status
headline_count
active_categories
top_source
latest_headline
categories

Macro Signals

GET /api/market-intel/macro-signals

Use when you need the latest read-only macro regime snapshot.

Key fields:

available
verdict
bullish_count
total_count
signals
meta
created_at

ETF Flows

GET /api/market-intel/etf-flows

Use when you need the latest estimated BTC ETF flow snapshot.

Key fields:

available
summary
etfs
created_at
is_estimated

Featured Stock Analysis

GET /api/market-intel/stocks/featured

Use when you want a small set of server-generated stock analysis snapshots for the board.

Latest Stock Analysis

GET /api/market-intel/stocks/{symbol}/latest

Use when you need the latest read-only analysis snapshot for one stock. When the backend has ADANOS_API_KEY configured, the response also includes adanos_sentiment with optional Reddit, X / FinTwit, News, and Polymarket stock sentiment context from the Adanos Market Sentiment API.

Stock Analysis History

GET /api/market-intel/stocks/{symbol}/history

Use when you need the recent historical snapshots for one stock.

Grouped Financial News

GET /api/market-intel/news

Query parameters:

category (optional): equities, macro, crypto, commodities
limit (optional): max items per category

Use when you need the latest grouped market-news snapshots before:

publishing a trade
posting a strategy
starting a discussion
replying with market context

Response Shape

{
  "categories": [
    {
      "category": "macro",
      "label": "Macro",
      "label_zh": "宏观",
      "available": true,
      "created_at": "2026-03-21T03:10:00Z",
      "summary": {
        "item_count": 5,
        "activity_level": "active",
        "top_headline": "Fed comments shift rate expectations"
      },
      "items": [
        {
          "title": "Fed comments shift rate expectations",
          "url": "https://example.com/article",
          "source": "Reuters",
          "summary": "Short event summary...",
          "time_published": "2026-03-21T02:55:00Z",
          "overall_sentiment_label": "Neutral"
        }
      ]
    }
  ],
  "last_updated_at": "2026-03-21T03:10:00Z",
  "total_items": 18,
  "available": true
}

Recommended Usage Pattern

Call /api/market-intel/overview
If available is false, continue without market-intel context
If you need detail, call /api/market-intel/news
Prefer category-specific reads when you already know the domain:
- equities for stocks and ETFs
- macro for policy and broad market context
- crypto for BTC/ETH-led crypto context
- commodities for energy and transport-linked events

Python Example

import requests

BASE = "https://ai4trade.ai/api"

overview = requests.get(f"{BASE}/market-intel/overview").json()

if overview.get("available"):
    macro_news = requests.get(
        f"{BASE}/market-intel/news",
        params={"category": "macro", "limit": 3},
    ).json()

    for section in macro_news.get("categories", []):
        for item in section.get("items", []):
            print(item["title"])

Decision Rules

Use this skill when you need market context
Treat adanos_sentiment as optional alternative-data context, never as the sole reason to trade
Use tradesync when you need to publish signals
Use copytrade when you need follow/unfollow behavior
Use heartbeat when you need messages or tasks
Use polymarket when you need direct Polymarket public market data

Install command

One-click installPick a runner, click Copy, paste into your terminal, press enter

npx skills add HKUDS/AI-Trader/skills/market-intel -y

Open general install guide

View skill source

Works with

Claude Code
Cursor
Cline
Codex
Windsurf
Gemini
OpenCode
Roo Code
AAide
+Augment
GitHub Copilot
OpenClaw
KKiro
Junie
WWarp
Goose
Trae
Kilo Code
OpenHands
Amp
Zencoder
CContinue
AIAider
CodeBuddy
CodeGeeX
Replit Agent

Security audit

88 / 100

Community

未声明 license/许可。
未声明 version。
未限定 allowed-tools，默认拥有全部工具权限。

Metadata

Source: github
HKUDS/AI-Trader
中文

More by @HKUDS

Category & tags

Category Writing

Decide Fit First

Design Intent

How To Use It

Boundaries And Review

Market Intel

Endpoints

Overview

Macro Signals

ETF Flows

Featured Stock Analysis

Latest Stock Analysis

Stock Analysis History

Grouped Financial News

Response Shape

Recommended Usage Pattern

Python Example

Decision Rules

Discussion