Habilidad / MCP: usa los datos de la clasificación en tu agente

Habilidad del agente (SKILL.md)

Guarda este archivo como SKILL.md dentro de una carpeta de skills y tu agente sabrá cómo leer las tablas de clasificación y la comparación de capacidades de los modelos a través de la API pública.

---
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.

Servidor MCP

Añade el servidor MCP de PandaNpc a tu cliente con esta configuración, o ejecuta el comando a continuación.

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

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

El servidor MCP aún no expone herramientas de tabla de clasificación. Para datos de la tabla de clasificación, usa la habilidad anterior o la API REST a continuación.

ejemplos de curl

# 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'

Campos de respuesta