zeta-data-source — for Claude Code zeta-data-source, zetaterminal, community, for Claude Code, ide skills, yfinance, to_thread, Terminal, Source, Integration

v1.0.0

Über diesen Skill

Perfekt für datenintensive KI-Agents, die eine umfassende Inhaltsanalyse und Integration mit mehreren Datenquellen über REST, aiohttp und Rate Limiting benötigen. Lokalisierte Zusammenfassung: Integrate a new external data source (market data, API, feed) following zetaterminal async patterns. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

Funktionen

Zeta Terminal — New Data Source Integration
Existing Sources (reference patterns)
Source File Pattern
-------- ------ ---------
MOEX ISS services/zcyc service.py REST + aiohttp, public API, no auth

# Core Topics

russiankendricklamar russiankendricklamar
[2]
[0]
Updated: 3/14/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 8/11

This page remains useful for teams, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution
Review Score
8/11
Quality Score
33
Canonical Locale
ru
Detected Body Locale
ru

Perfekt für datenintensive KI-Agents, die eine umfassende Inhaltsanalyse und Integration mit mehreren Datenquellen über REST, aiohttp und Rate Limiting benötigen. Lokalisierte Zusammenfassung: Integrate a new external data source (market data, API, feed) following zetaterminal async patterns. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

Warum diese Fähigkeit verwenden

Ermöglicht es Agenten, neue Datenquellen über REST, aiohttp und Rate Limiting zu integrieren, wodurch eine nahtlose Interaktion mit öffentlichen APIs, authentifizierten Diensten und Bibliotheken wie yfinance ermöglicht wird, während gleichzeitig die Rate Limiting für Dienste wie RuData/Interfax

Am besten geeignet für

Perfekt für datenintensive KI-Agents, die eine umfassende Inhaltsanalyse und Integration mit mehreren Datenquellen über REST, aiohttp und Rate Limiting benötigen.

Handlungsfähige Anwendungsfälle for zeta-data-source

Integration von Finanzdaten von Yahoo Finance unter Verwendung der Bibliothek yfinance
Abruf von Daten von MOEX ISS über REST und aiohttp
Verwaltung von ratebegrenzten Anfragen für RuData/Interfax mit authentifiziertem Zugriff

! Sicherheit & Einschränkungen

  • Benötigt eine Python-Umgebung
  • Abhängig von der Verfügbarkeit und Authentifizierung externer Datenquellen
  • Rate Limiting-Einschränkungen gelten für bestimmte Datenquellen wie RuData/Interfax

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.
  • - The underlying skill quality score is below the review floor.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Labs Demo

Browser Sandbox Environment

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Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is zeta-data-source?

Perfekt für datenintensive KI-Agents, die eine umfassende Inhaltsanalyse und Integration mit mehreren Datenquellen über REST, aiohttp und Rate Limiting benötigen. Lokalisierte Zusammenfassung: Integrate a new external data source (market data, API, feed) following zetaterminal async patterns. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

How do I install zeta-data-source?

Run the command: npx killer-skills add russiankendricklamar/zetaterminal/zeta-data-source. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for zeta-data-source?

Key use cases include: Integration von Finanzdaten von Yahoo Finance unter Verwendung der Bibliothek yfinance, Abruf von Daten von MOEX ISS über REST und aiohttp, Verwaltung von ratebegrenzten Anfragen für RuData/Interfax mit authentifiziertem Zugriff.

Which IDEs are compatible with zeta-data-source?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for zeta-data-source?

Benötigt eine Python-Umgebung. Abhängig von der Verfügbarkeit und Authentifizierung externer Datenquellen. Rate Limiting-Einschränkungen gelten für bestimmte Datenquellen wie RuData/Interfax.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add russiankendricklamar/zetaterminal/zeta-data-source. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use zeta-data-source immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

zeta-data-source

Lokalisierte Zusammenfassung: Integrate a new external data source (market data, API, feed) following zetaterminal async patterns. This AI agent skill

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

Zeta Terminal — New Data Source Integration

Existing Sources (reference patterns)

SourceFilePattern
MOEX ISSservices/zcyc_service.pyREST + aiohttp, public API, no auth
RuData/Interfaxservices/rudata_service.pyREST + rate limiting (5 req/s), auth token
Yahoo Financeservices/spectral_regime_service.pyyfinance library, sync wrapped in to_thread

Service Template

backend/src/services/{source}_service.py:

python
1""" 2{Source Name} data service. 3 4API docs: {url} 5Rate limits: {X req/s} 6Auth: {method} 7""" 8import logging 9import aiohttp 10from typing import Any 11 12logger = logging.getLogger(__name__) 13 14# Constants 15BASE_URL = "https://api.example.com" 16TIMEOUT = aiohttp.ClientTimeout(total=30) 17MAX_RETRIES = 3 18 19 20class {Source}Service: 21 """Async client for {Source} API.""" 22 23 def __init__(self, api_key: str | None = None): 24 self.api_key = api_key 25 self._session: aiohttp.ClientSession | None = None 26 27 async def _get_session(self) -> aiohttp.ClientSession: 28 if self._session is None or self._session.closed: 29 headers = {"Content-Type": "application/json"} 30 if self.api_key: 31 headers["Authorization"] = f"Bearer {self.api_key}" 32 self._session = aiohttp.ClientSession( 33 base_url=BASE_URL, 34 headers=headers, 35 timeout=TIMEOUT, 36 ) 37 return self._session 38 39 async def fetch_data(self, params: dict[str, Any]) -> dict[str, Any]: 40 """ 41 Fetch data from {Source}. 42 43 Parameters 44 ---------- 45 params : dict 46 Query parameters. 47 48 Returns 49 ------- 50 dict with keys: data, metadata 51 52 Raises 53 ------ 54 ValueError 55 If API returns an error or invalid data. 56 RuntimeError 57 If connection fails after retries. 58 """ 59 session = await self._get_session() 60 61 for attempt in range(MAX_RETRIES): 62 try: 63 async with session.get("/endpoint", params=params) as resp: 64 if resp.status != 200: 65 text = await resp.text() 66 logger.error("{Source} API error %d: %s", resp.status, text) 67 if resp.status == 429: # Rate limited 68 await asyncio.sleep(2 ** attempt) 69 continue 70 raise ValueError(f"{Source} API returned {resp.status}") 71 72 data = await resp.json() 73 return self._parse_response(data) 74 except aiohttp.ClientError as e: 75 logger.error("{Source} connection error (attempt %d): %s", attempt + 1, e) 76 if attempt == MAX_RETRIES - 1: 77 raise RuntimeError(f"{Source} unavailable after {MAX_RETRIES} retries") from e 78 79 def _parse_response(self, raw: dict) -> dict[str, Any]: 80 """Parse and validate API response.""" 81 # Transform to standard format 82 return { 83 "data": raw, 84 "metadata": { 85 "source": "{source}", 86 "timestamp": datetime.now(datetime.UTC).isoformat(), 87 } 88 } 89 90 async def close(self): 91 if self._session and not self._session.closed: 92 await self._session.close()

Router Pattern

python
1@router.get("/api/{source}/fetch") 2async def fetch_data( 3 param: str = Query(..., description="Query parameter"), 4): 5 service = {Source}Service(api_key=os.environ.get("{SOURCE}_API_KEY")) 6 try: 7 result = await service.fetch_data({"param": param}) 8 return result 9 except ValueError as e: 10 raise HTTPException(status_code=400, detail=str(e)) from e 11 except RuntimeError as e: 12 raise HTTPException(status_code=503, detail="Data source unavailable") from e 13 finally: 14 await service.close()

Data Source Priorities (Aladdin Data Platform roadmap)

SourceDataPriority
CBR (ЦБ РФ)Ключевая ставка, инфляция, денежная массаP1
FREDUS macro (GDP, CPI, Fed Funds Rate)P1
BinanceCrypto prices, order bookP2
MOEX ISS (расширение)Акции, фьючерсы, индексыP1
FinamИсторические данные российских акцийP2

Checklist Before Done

  • Async client with aiohttp (not requests)
  • Retry logic with exponential backoff
  • Rate limiting respected (429 handling)
  • API key from os.environ, never hardcoded
  • Timeout configured (aiohttp.ClientTimeout)
  • Session cleanup (close() method)
  • Response parsed into standard format (data + metadata)
  • Router with proper error handling (400/503)
  • API docs URL in docstring
  • ruff check passes

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