本文へ移動
cccskills
無料GitHub で公開

spark-ai-models

Use when adding or updating Spark AI provider models or their compact and preflight metrics, especially baidu-oneapi, Grok, Claude, GPT, DeepSeek, OneAPI, context windows, output budgets, prices, thinking maps, or transports.

インストール方法を見る

含まれるファイル(2)

  • SKILL.md3.2 KB
  • reference.md4.4 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Spark AI model catalog

Owner: packages/spark-llm-providers. Catalog, gateway rewrites, and measured windows live in baidu-oneapi.ts. Do not guess vendor ids, context, or prices.

Workflow

  1. Identify the change: new model, metric correction, or both.
  2. Research current vendor docs (and gateway ids). Record source URLs and the exact numbers. If docs conflict with a live gateway, keep both in comments and register the gateway ceiling for contextWindow.
  3. Edit the existing provider owner. For Baidu, follow reference.md. Do not add a second catalog or public alias.
  4. If this is a successor model, replace the predecessor in default enable (see Baidu OneAPI). Update tests and packages/spark-llm-providers/README.md.
  5. Run the package and registry tests listed in the reference.

Research rules

  • Prefer the vendor's current model and pricing pages over training memory, blogs, or aggregator tables.
  • Model id uses a dot when the vendor does (grok-4.6, not grok-4-6).
  • contextWindow is the prompt+output ceiling Spark compact/preflight uses. On Baidu, measured provider input beats advertised vendor context.
  • maxTokens is Spark's output budget, not always the vendor max. If the vendor lists no output cap, keep the same-family budget unless measurement says otherwise.
  • Spark cost is USD per million tokens: { input, output, cacheRead, cacheWrite }. Use headline rates (Baidu/Spark do not model xAI ≥200k 2× long-context pricing). If the vendor has no cache-write fee, set cacheWrite to the input rate like existing Grok rows.
  • thinkingLevelMap only remaps Spark levels that differ from the transport. Confirm whether xhigh is real, aliased to high, or invalid.

Baidu OneAPI

  • Claude and DeepSeek → anthropic-messages. GPT-5.6 and Grok → openai-responses (BAIDU_ONEAPI_OPENAI_RESPONSES_MODEL_IDS).
  • Local id and gateway id can differ (claude-opus-5 → Opus 5). GPT/Grok are currently 1:1.
  • Adding a model also requires GATEWAY_MODEL_BY_ID plus the models[] row.
  • Catalog and default enable are separate. Keep the predecessor catalog row unless the user asks to delete it. Default enabledModels is the current frontier only: when a successor ships (grok-4.5 → grok-4.6), replace the old id in DEFAULT_SPARK_ENABLED_MODEL_PATTERNS with the new one. Do not leave both enabled, and do not use baidu-oneapi/*.
  • Add the previous bundled default (including baidu-oneapi/*) as a legacy set that migrates onto the new list. A user's custom scope, such as baidu-oneapi/* alone, must not be rewritten.
  • Prove default enable with membership tests: new id in enabledModelIds, old id out. Do not freeze the whole catalog as the scope contract.

Metric edits

Changing only windows or prices still needs tests and README notes. Do not advertise a round number (1M, 256k) when the gateway hard-fails earlier.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Use when Spark engineering knowledge must be placed, deduplicated, migrated, or validated across AGENTS, Notes, Roles, Skills, and Workflows.

日本語の概要は準備中です。原文の説明を表示しています。

zendev-lab/spark22026年10月11日 更新

Use when a Spark change needs its authoritative owner, affected boundaries, risks, acceptance criteria, and smallest verifiable slice established before implementation or review.

日本語の概要は準備中です。原文の説明を表示しています。

zendev-lab/spark22026年10月11日 更新

Use when a Spark implementation needs an evidence-based review for correctness, ownership, compatibility, failure handling, maintainability, and unnecessary complexity.

日本語の概要は準備中です。原文の説明を表示しています。

zendev-lab/spark22026年10月11日 更新

Use when a Spark feature needs repository-first research, explicit option selection, and an owner-aligned implementation plan before code changes.

日本語の概要は準備中です。原文の説明を表示しています。

zendev-lab/spark22026年10月11日 更新

Use when a working Spark implementation should be simplified without changing its observed behavior, ownership, compatibility, or public contract.

日本語の概要は準備中です。原文の説明を表示しています。

zendev-lab/spark22026年10月11日 更新

Use when a running Spark or DSH web service needs real-browser verification — page load, client-plugin boot errors, console errors, failed requests, or onboarding/dialog rendering — with the repository's own Playwright chromium.

日本語の概要は準備中です。原文の説明を表示しています。

zendev-lab/spark22026年10月11日 更新

zendev-lab のスキルをすべて見る

このスキルの問題を報告する