القائمة
Generate a structured Markdown report using notebookmd. Use when the user asks for a report, documentation, summary, or writeup that should be saved as a formatted Markdown file with sections, tables, metrics, and artifacts.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Generate a structured data analysis report using notebookmd. Use when the user asks to analyze data, a CSV file, a DataFrame, financial data, or any dataset and wants a readable Markdown report with tables, charts, metrics, and insights.
Generate a metrics dashboard using notebookmd with KPIs, charts, and data tables. Use when the user wants a dashboard, scorecard, or metrics overview saved as Markdown.
Reference guide for the notebookmd library API. Use when you need to look up notebookmd widget methods, check API signatures, or understand how to use a specific notebookmd feature. This skill provides the complete API reference.
| name | report |
| description | Generate a structured Markdown report using notebookmd. Use when the user asks for a report, documentation, summary, or writeup that should be saved as a formatted Markdown file with sections, tables, metrics, and artifacts. |
| argument-hint | [topic or description] |
| allowed-tools | ["Bash","Read","Write","Edit","Glob","Grep"] |
Generate a structured, professional Markdown report using the notebookmd library.
Report topic: $ARGUMENTS
from notebookmd import nb, NotebookConfig
n = nb("dist/report.md", title="<descriptive title>")
Adapt the structure to the topic. Common patterns:
Executive Summary Pattern:
n.section("Executive Summary")
n.metric_row([...]) # Top-line KPIs
n.write("Brief overview...")
n.section("Background")
n.write("Context and motivation...")
n.section("Methodology")
with n.expander("Details"):
n.write("Step-by-step approach...")
n.section("Results")
n.table(results_df, name="Key Results")
n.kv(metrics_dict, title="Performance Metrics")
n.section("Conclusion")
n.success("Summary of outcomes")
Technical Report Pattern:
n.section("Overview")
n.kv(config_dict, title="Configuration")
n.section("Implementation")
n.code(code_snippet, lang="python")
n.note("Key technical detail...")
n.section("Results")
n.table(benchmarks_df, name="Benchmarks")
n.section("Next Steps")
n.write("1. Item one\n2. Item two")
Status Report Pattern:
n.section("Status Overview")
n.metric_row([
{"label": "Complete", "value": "73%", "delta": "+5%"},
{"label": "On Track", "value": "12/15"},
{"label": "Blocked", "value": "2"},
])
n.section("Completed This Period")
n.write("- Task 1\n- Task 2")
n.section("In Progress")
n.progress(0.73, "Overall completion")
n.write("Current work items...")
n.section("Risks & Blockers")
n.warning("Risk description...")
n.error("Blocker description...")
Text: n.title(), n.header(), n.subheader(), n.write(), n.md(), n.caption(), n.code(), n.latex(), n.text()
Data: n.metric(), n.metric_row(), n.table(), n.dataframe(), n.kv(), n.json(), n.summary()
Status: n.success(), n.error(), n.warning(), n.info(), n.progress(), n.badge()
Layout: n.section(), n.expander(), n.tabs(), n.divider()
Analytics: n.stat(), n.stats(), n.change(), n.ranking()
Charts: n.line_chart(), n.bar_chart(), n.area_chart(), n.figure()
Export: n.save(), n.to_markdown(), n.export_csv()
out = n.save()
print(f"Report saved to: {out}")