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lorcana-mcp-platform: Skill for Cursor

.cursor/skills/lorcana-card-analysis/SKILL.md

lorcana-card-analysis is a skill for Cursor from kschltz/lorcana-mcp-platform. It costs 122 tokens per session (1,291 once invoked), scanned A, original, MIT.

A Portuguese-language research tool for Disney Lorcana cards and decks, using real card data, prices, public decklists, and meta information. Disney Lorcana is a collectible trading card game.

In plain words
What is it for?
Use it to analyze cards, compare them, find synergies, build or assess decks, review competitive trends, and test decklists against an AI in the browser.
Why use it?
It brings card details and current deck information together for comparisons and deck decisions.

Skill for Cursor

Written for Cursor: installed under .cursor/.

This is kschltz/lorcana-mcp-platform's own configuration. It tells Cursor how to work on lorcana-mcp-platform itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything lorcana-mcp-platform configures →

not rated 0repo 3mo ago A scan 122 tokens original MIT
View source ↗ kschltz/lorcana-mcp-platform
Reuse

Borrowing it

Nothing to install: this file belongs to kschltz/lorcana-mcp-platform. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/kschltz/lorcana-mcp-platform/main/.cursor/skills/lorcana-card-analysis/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/kschltz/lorcana-mcp-platform

Made for: Cursor.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for lorcana-card-analysis

README.md
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Your own site
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Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

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Your own site · 80×15
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Per session 122 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,291 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00122 $0.01291
Opus 5.5 $0.00049 $0.00516
Sonnet 5.5 $0.00024 $0.00258
Haiku 4.5 $0.00012 $0.00129

Measured 2mo ago against content hash bd526d1b8008, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

lorcana-card-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/lorcana_lookup.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.cursor/skills/lorcana-card-analysis/SKILL.md · 54 lines

How it starts

The opening of the file, as written. The whole thing — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Lorcana Card Analysis

Análise profunda de cartas e decks de Disney Lorcana baseada em dados reais de duas fontes complementares:

  • lorcana-api.com — texto completo das cartas (habilidades, traits, flavor), atributos e bulk de todos os sets. Cobertura: sets 1–12.
  • dreamborn.ink — mais atualizada (set mais recente), preços em USD, decks públicos do meta com arquétipos/likes, decklists completas.
  • inktable.net/lor (Ink Table) — playground de playtest: simulador gratuito no navegador para jogar a decklist contra IA, sem instalação nem conta. Aceita importação de lista em texto (formato dreamborn/pixelborn). Aponte como destino de teste ao entregar decks. Se o usuário pedir para jogar/testar a partida você mesmo, siga references/inktable-playtest.md (automação Playwright completa: setup com bloqueio de anúncios, importação, interação de cliques, leitura do log, gravação de vídeo).

Ferramentas

Use scripts/lorcana_lookup.py (stdlib apenas) para toda consulta — não escreva requests ad hoc:

python3 scripts/lorcana_lookup.py card "Elsa" --title "Spirit of Winter" [--set TFC]
python3 scripts/lorcana_lookup.py search color=Ruby rarity=Legendary [set-code=WUN]
python3 scripts/lorcana_lookup.py bulk                 # salva /tmp/lorcana_bulk.json
python3 scripts/lorcana_lookup.py decks [--max-results 10]
python3 scripts/lorcana_lookup.py deck <id-do-deck>    # decklist completa + preço + descrição

Referências (leia conforme a necessidade):

  • references/lorcana-api.md — endpoints, modelos de dados e diferenças strict vs bulk.
  • references/dreamborn.md — endpoints, modelo de carta, decks/meta, formato de decklist em texto.
  • references/inktable-playtest.md — como jogar partidas reais no Ink Table via Playwright (leia quando o usuário pedir para testar/jogar um deck contra a IA).

Fluxo de análise de uma carta

  1. Perfil: card no script — funde as duas fontes (texto de habilidades vem do lorcana-api; variants/raridade/preço de mercado do dreamborn). Se a carta não existir no lorcana-api (set muito novo), use só dreamborn e busque o texto na web.
  2. Benchmark de stats: baixe o bulk uma vez e compare a carta com a coorte de mesmo custo/ink (localmente, com pandas ou Python): strength+willpower+lore vs. custo, taxa de inkables, curva padrão do custo. A vanilla test: cartas inkable com stats na curva + habilidade forte = premium; uninkable precisa de habilidade claramente acima da curva.
  3. Texto e keywords: avalie habilidades pelo impacto em jogo (draw/ramp/removal/proteção), custo de ativação, e keywords (Evasive, Ward, Shift, Rush, Challenger, Resist, Singer...). Sinergias: busque outras cartas da mesma classificação/nome/franquia via search ou grep no bulk (ex. todas as "Puppy", todos os "Musketeer").
  4. Contexto de meta: decks lista decks públicos populares; deck <id> traz a lista completa, o preço total e a descrição do criador (plano de jogo). Verifique se a carta aparece em decks com muitos likes/views do mesmo arquétipo.
  5. Formato legal: campo formats dos decks (1 = Core, 2 = Infinity). Para Core, confirme se a carta é dos sets válidos no momento.

Read the full file on GitHub · 54 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2mo ago First seen · 54 lines · 122 tokens per session scan A bd526d1b8008

Subscribe to this mod's changes

lorcana-card-analysis is a skill published in the GitHub repository kschltz/lorcana-mcp-platform (0 stars, last pushed 3mo ago), licensed MIT. It adds 122 tokens to every session and 1,291 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Game developmentResearch
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