AgentSkillsCN

reporting-pipelines

支持 CSV/JSON/Markdown 导出的报告流水线，可生成带时间戳的输出、摘要，并进行后续处理。

SKILL.md
--- frontmatter
name: reporting-pipelines
description: Reporting pipelines for CSV/JSON/Markdown exports with timestamped outputs, summaries, and post-processing.
version: 1.0.0
category: universal
author: Claude MPM Team
license: MIT
progressive_disclosure:
  entry_point:
    summary: "Generate CSV/JSON/markdown reports with timestamped filenames and summary outputs."
    when_to_use: "Building reporting flows, exporting analytics results, or standardizing CSV/JSON/markdown outputs across projects."
    quick_start: "1. Run the CLI that produces base data 2. Export CSV/JSON/markdown with timestamps 3. Save to reports/"
tags:
  - reporting
  - csv
  - json
  - markdown
  - analytics

Reporting Pipelines

Overview

Your reporting pattern is consistent across repos: run a CLI or script that emits structured data, then export CSV/JSON/markdown reports with timestamped filenames into reports/ or tests/results/.

GitFlow Analytics Pattern

bash
# Basic run
gitflow-analytics -c config.yaml --weeks 8 --output ./reports

# Explicit analyze + CSV
gitflow-analytics analyze -c config.yaml --weeks 12 --output ./reports --generate-csv

Outputs include CSV + markdown narrative reports with date suffixes.

EDGAR CSV Export Pattern

edgar/scripts/create_csv_reports.py reads a JSON results file and emits:

  • •executive_compensation_<timestamp>.csv
  • •top_25_executives_<timestamp>.csv
  • •company_summary_<timestamp>.csv

This script uses pandas for sorting and percentile calculations.

Standard Pipeline Steps

  1. •Collect base data (CLI or JSON artifacts)
  2. •Normalize into rows/records
  3. •Export CSV/JSON/markdown with timestamp suffixes
  4. •Summarize key metrics in stdout
  5. •Store outputs in reports/ or tests/results/

Naming Conventions

  • •Use YYYYMMDD or YYYYMMDD_HHMMSS suffixes
  • •Keep one output directory per repo (reports/ or tests/results/)
  • •Prefer explicit prefixes (e.g., narrative_report_, comprehensive_export_)

Troubleshooting

  • •Missing output: ensure output directory exists and is writable.
  • •Large CSVs: filter or aggregate before export; keep summary CSVs for quick review.

Related Skills

  • •universal/data/sec-edgar-pipeline
  • •toolchains/universal/infrastructure/github-actions