reporting-workflow
End-to-end workflow for generating reports from data, validating outputs, running report-focused tests, and iterating on HTML/interactive reporting artifacts.
Best use case
reporting-workflow is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
End-to-end workflow for generating reports from data, validating outputs, running report-focused tests, and iterating on HTML/interactive reporting artifacts.
Teams using reporting-workflow should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/reporting-workflow/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How reporting-workflow Compares
| Feature / Agent | reporting-workflow | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
End-to-end workflow for generating reports from data, validating outputs, running report-focused tests, and iterating on HTML/interactive reporting artifacts.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Reporting Workflow ## When to Use Use this skill when a task follows the common pattern: 1. inspect the input data/model/output expectations 2. run a report generator 3. open or validate the generated artifact 4. run targeted tests 5. refine the report if structure, visuals, or data mappings are wrong Typical cases: - benchmark reports - engineering summary reports - interactive HTML dashboards - validation reports with plots/tables ## Core Workflow ### 1. Inspect Inputs and Existing Patterns Read the generator, input schema, and one known-good output first. ```bash # inspect generator and fixtures rg -n "report|dashboard|html" examples/ tests/ scripts/ ``` Check for: - required inputs and file locations - expected output paths - linked assets (plots, CSS, JS, images) - existing tests or snapshots ### 2. Generate the Report Run the narrowest generator command possible. ```bash # generic pattern uv run --no-project python path/to/generator.py # if shell wrapper exists bash path/to/generate-report.sh ``` Capture: - output file path - warnings/errors - whether the file was regenerated or unchanged ### 3. Verify the Artifact For HTML outputs, use structural + visual verification. Preferred checks: - file exists and is non-empty - expected headings/sections are present - expected charts/tables rendered - no obvious console/JS failures If the output is HTML, pair with: - `html-report-verify` ### 4. Run Report-Focused Tests Use the smallest test slice that covers the report workflow. ```bash uv run pytest tests/reporting/ -q # or a targeted file/case uv run pytest tests/path/test_report_x.py::test_generates_expected_sections -q ``` If no report test exists yet: - add a focused regression test for the bug or missing section - prefer structural assertions over brittle full-file diffs unless snapshots are already standard ### 5. Iterate on Generator / Template / Data Mapping Common failure buckets: - wrong data aggregation - missing section wiring - broken template variables - invalid asset paths - JS/chart rendering failures - report generated but not linked into navigation/index pages Fix one layer at a time: - data extraction - transformation - template rendering - final asset packaging ### 6. Re-run Validation After each fix: - regenerate - re-run targeted tests - re-verify final artifact Do not stop at “generator exited 0” — confirm the report is actually correct. ## Recommended Validation Ladder 1. script exits successfully 2. output file exists 3. structural assertions pass 4. targeted tests pass 5. visual/HTML verification passes when relevant ## Test Integration Guidance Prefer tests that assert: - key section headings exist - expected records/counts appear - chart containers exist - critical summary metrics match fixture inputs Avoid overly fragile tests that fail on harmless formatting changes unless snapshot testing is already expected. ## Integration Notes This skill complements: - `html-report-verify` for visual/DOM verification - `interactive-report-generator` for richer dashboard/report generation patterns - `engineering-report-generator` for engineering-specific outputs ## Common Pitfalls - regenerating without checking the output path - trusting console-clean output without opening the report - testing only generator internals instead of final artifact structure - mixing data bugs and template bugs in one change - forgetting to add regression coverage for a discovered report bug
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