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Turn an Excel workbook into business insight: structured read → trend/anomaly summary → write back to a new 'Insights' sheet → persist KPIs to memory.
デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。
インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/TokenRhythm/opensquilla --skill meta-spreadsheet-insightコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか？SkillsMP が現在取得できるファイルをダウンロードできます。
Query scholarly metadata and the web through Crossref, Brave, Tavily, and DuckDuckGo with a single CLI surface. Trigger when the user asks for research search, fact lookup, source discovery, or engine comparison. Results retain DOI, publication year, and authors when supplied by Crossref, then deduplicate by DOI, arXiv ID, or normalized URL. API-key engines gate themselves on the relevant environment variable; Crossref and DuckDuckGo need no key.
Deterministic OpenRouter image generation adapter for Nano Banana Pro / Gemini image models. Use as skill_exec when a meta-skill needs local image files and structured IMAGE_READY records without spawning an LLM agent.
Generate or edit a single image via OpenRouter (google/gemini-3.1-flash-image-preview by default). Accepts a text prompt and optional --input-image for image-to-image editing. Trigger when the user asks for an AI image, illustration, concept art, product render, or wants to modify an existing image.
SOC 職業分類に基づく
SKILL.md を表示中
| name | meta-spreadsheet-insight |
| description | Turn an Excel workbook into business insight: structured read → trend/anomaly summary → write back to a new 'Insights' sheet → persist KPIs to memory. |
| kind | meta |
| meta_priority | 55 |
| always | false |
| triggers | ["spreadsheet insight","excel 分析","xlsx 洞察","数据复盘"] |
| provenance | {"origin":"opensquilla-original","license":"Apache-2.0"} |
| composition | {"steps":[{"id":"read","skill":"xlsx","with":"[Truncated]"},{"id":"analyze","skill":"summarize","depends_on":"[Truncated]","with":"[Truncated]"},{"id":"writeback","skill":"xlsx","depends_on":"[Truncated]","with":"[Truncated]"},{"id":"memorize","kind":"tool_call","tool":"memory_save","tool_allowlist":"[Truncated]","depends_on":"[Truncated]","tool_args":"[Truncated]"}]} |
Reads a workbook, computes a structured trend / anomaly analysis, writes the result back as a new sheet, and persists key KPIs to long-term memory.
LLM should call xlsx read, summarize, xlsx append, then memory_save.
