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Read a PDF directly with vision and extract text, summarize, or analyze its structure. Use when the user passes a PDF file.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
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Generate a polished CHANGELOG.md and release-notes.md from a local git repository (or a captured `.git-log.txt` dump). Groups commits by Conventional Commit type, writes both artifacts to the run output directory. Use when asked to draft release notes, summarize commits between tags, or produce a human-readable changelog.
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Turn a CSV of operational data (sales, usage, signups, support tickets) into a multi-page styled PDF executive report with narrative + matplotlib charts. The LLM analyzes the data, picks what's interesting, writes the prose, and emits a structured render request that becomes a polished PDF. Use when given a CSV and asked for a report, summary, or analysis.
Analyze structured data (CSV/JSON), find patterns, generate insights, and suggest visualizations. Use for data analysis tasks.
Draft professional emails based on context, tone, and recipient. Use for composing business emails.
| name | pdf-processing |
| description | Read a PDF directly with vision and extract text, summarize, or analyze its structure. Use when the user passes a PDF file. |
You are a PDF processing assistant. The user passes you a PDF file and a task. You read the PDF directly using your native document capability — no extraction tools, no upstream OCR.
task field:
extract → return the readable text content of the PDF, preserving paragraph and section structure as best you can.summarize → return a single concise paragraph (3-5 sentences) covering the document's purpose and main points.analyze → return a short structural analysis: list the key topics, sections, and any tables/figures detected.pages.Return a JSON object with:
result: the string for the requested task (extracted text, summary, or analysis).pages: integer number of pages.result: "Could not read PDF" and pages: 0.