스킬 / MCP: 에이전트에서 리더보드 데이터 사용

에이전트 스킬 (SKILL.md)

이 파일을 skills 폴더 안에 SKILL.md로 저장하면, 당신의 에이전트가 공개 API를 통해 리더보드와 모델 기능 비교를 읽는 방법을 알게 됩니다.

---
name: pandanpc-leaderboard
description: Look up current AI model leaderboards and the top-10 model capability comparison from PandaNpc's public API. Use when the user asks which AI model is best, how models rank on chat, coding, image, video, speech or agent tasks, or how top models compare on benchmarks.
---

# PandaNpc leaderboard

Public, read-only JSON API. No account and no API key. Base URL: https://api.pandanpc.com/api/public/leaderboard

## Boards

GET https://api.pandanpc.com/api/public/leaderboard
GET https://api.pandanpc.com/api/public/leaderboard?category=<board key>

Response: { boards: [{ key, source, metric, meta, rows }], vendorIcons }
- With ?category=<key> the response still contains every board, but only the requested one has rows; boards with an empty rows array are shells. Always pick a board by key (for example jq '.boards[] | select(.key=="llm_chat")'), never by index.
- key: llm_chat, image_gen, code, image_edit, video, agent, vision, search, document, image_to_video, video_edit, text_to_speech, speech_to_text, speech_to_speech, or_usage, aa_intelligence
- source: arena | artificial_analysis | openrouter
- meta: { source_url, last_updated, synced_at }
- rows: [{ rank, model, vendor, score, ci, votes, ...price fields }]

Scores are comparable only inside one board. Arena boards are Elo from human blind votes; read the rank together with ci. Lower is better for speech-to-text (word error rate).

## Capability comparison

GET https://api.pandanpc.com/api/public/leaderboard/capabilities

Response: { dimensions, models, sources, fetched_at }
- models: top 10 by Epoch Capabilities Index: { rank, model, model_key, vendor, eci }
- sources: [{ source, label, license, url, updated, fetched_at, boards }] including epoch, vals, aa, google_card, browserbase, browser_use, coarena and ale
- boards: [{ key, name, capability, comparison_key, updated, fetched_at, scores }] where scores is keyed by model_key: { score, score_raw, scale, effort, harness, cost_per_task, model_version, evaluation_metadata }

Preserve every published configuration. Compare only within one source and comparison_key. Read scale: percent is 0-100, rating (Coarena) is not a percentage. Coarena is mixed-task blind human preference; show its 95% interval. ALE allows GUI/CLI tools; keep its full/max configuration, harness and run-task / split-task counts, and separate pass rate from partial score. updated is the upstream date when published; fetched_at is PandaNpc's fetch time, never a substitute source date.

## Attribution (required)

Name the source next to any number you show:
- Epoch AI, CC BY 4.0 (epoch.ai)
- Vals.ai (vals.ai)
- Artificial Analysis (artificialanalysis.ai)
- Coarena (coarena.ai) and Agents’ Last Exam, CC BY 4.0 (agents-last-exam.org), for their matching sources
- arena.ai and OpenRouter for the matching boards

Data refreshes about once a day. Cache for at least an hour.

MCP 서버

이 구성으로 PandaNpc MCP 서버를 클라이언트에 추가하거나 아래 명령을 실행하세요.

{
  "mcpServers": {
    "pandanpc": {
      "command": "npx",
      "args": ["-y", "@pandanpc/mcp-server"]
    }
  }
}

claude mcp add pandanpc -- npx -y @pandanpc/mcp-server

MCP 서버는 아직 리더보드 도구를 제공하지 않습니다. 리더보드 데이터에는 위의 스킬이나 아래의 REST API를 사용하세요.

curl 예제

# All boards (Arena, Artificial Analysis, OpenRouter) in one response
curl -s https://api.pandanpc.com/api/public/leaderboard

# One board: add ?category=<board key>, e.g. llm_chat, code, image_gen, aa_intelligence
# The response still lists every board, but only the requested one has rows (the others are empty shells)
curl -s "https://api.pandanpc.com/api/public/leaderboard?category=llm_chat"

# Top 5 models of the chat board: select the board by its key, never by position
curl -s "https://api.pandanpc.com/api/public/leaderboard?category=llm_chat" | jq '.boards[] | select(.key=="llm_chat") | .rows[:5] | map({rank, model, vendor, score})'

# Capability comparison: top 10 models by Epoch Capabilities Index x benchmarks
curl -s https://api.pandanpc.com/api/public/leaderboard/capabilities

# GPQA Diamond score of every model (Epoch AI)
curl -s https://api.pandanpc.com/api/public/leaderboard/capabilities | jq '.sources[] | select(.source=="epoch") | .boards[] | select(.key=="gpqa_diamond") | .scores'

응답 필드