Report Apiview Metrics Agent Skill
Run APIView platform metrics (versioned revisions and cross-language compliance). Use for: apiview metrics, platform metrics, version coverage, versioned revisions, cross-language compliance, compliance metrics, PackageVersion coverage, CrossLanguagePackageId, apiview-metrics, parser compliance.
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/Azure/azure-sdk-tools --skill report-apiview-metricsThe instruction itself
11 sections, as written by the authorReport APIView Metrics
When to Use
- Monitoring progress toward 100% versioned revisions across languages
- Checking cross-language metadata compliance (CrossLanguagePackageId)
- Generating trend charts for APIView platform health
- Reviewing parser compliance over time
What It Produces
A combined report with two metric buckets:
| Bucket | What it measures |
|--------|-----------------|
| versions | % of revisions with a valid PackageVersion, broken out by language and revision type (Automatic, Manual, PullRequest) |
| compliance | % of reviews whose latest revision includes CrossLanguagePackageId (from CrossLanguageMetadata) |
Output is JSON with top-level "versions" and "compliance" keys. With --summary, human-readable tables are printed to stderr.
Defaults
Unless the user says otherwise, always apply these defaults:
- Environment:
production - Months:
6 - Languages: Python, C#, Java, JavaScript, Go (all included by default — do not pass
--languagesunless user restricts) - Chart: Include
--chartunless user says no charts
Running the Command
Step 1: Run the Command
Show the resolved command and run it immediately in a foreground terminal with a 120-second timeout (timeout: 120000). Clean up stale output first.
New-Item -ItemType Directory -Path output -Force | Out-Null; New-Item -ItemType Directory -Path output/charts -Force | Out-Null; if (Test-Path output/apiview_metrics_output.json) { Remove-Item output/apiview_metrics_output.json }; python cli.py report apiview-metrics --chart --summary 2>$null | Out-File -Encoding UTF8 output/apiview_metrics_output.json
After the command completes, read the output file with read_file to get the JSON results. Then use view_image to display charts at:
output/charts/apiview_version_trends.pngoutput/charts/cross_language_compliance.png
Examples
# Default: 6 months, all languages, production, with charts
python cli.py report apiview-metrics --chart
# With human-readable summary tables on stderr
python cli.py report apiview-metrics --chart --summary
# Custom lookback
python cli.py report apiview-metrics --months 3 --chart
# Specific end date
python cli.py report apiview-metrics --months 6 --end-date 2026-04-30 --chart
# Specific languages only
python cli.py report apiview-metrics --languages Python Java --chart
# Staging environment
python cli.py report apiview-metrics --chart --environment staging
Step 2: Present Results
After reading the output file:
- Summarize the version-coverage trends (highlight languages below 100%)
- Summarize the compliance trends (highlight languages below 100%)
- Show the chart images with
view_image
Step 3: Answer Follow-up Questions
For follow-up questions about the same data, read the output file instead of re-running the command.
Available Flags
| Flag | Type | Default | Description |
|------|------|---------|-------------|
| --months | int | 6 | Number of calendar months to look back from end date |
| --end-date / -e | string | today | Inclusive query end date (YYYY-MM-DD) |
| --languages | list | all 5 | Space-separated language names to include |
| --chart | flag | off | Generate PNG trend charts to output/charts/ |
| --summary | flag | off | Print human-readable summary tables to stderr |
| --environment | string | production | production or staging |
Gotchas
- Redirect stdout to a file: Always pipe through
| Out-File -Encoding UTF8 output/apiview_metrics_output.json. Do NOT use>which produces UTF-16 in PowerShell 5.1. - Do NOT use
2>&1: This merges stderr log lines into the JSON output, producing invalid JSON. - Clean up before running: Delete previous output files before running to avoid presenting stale results.
- Use
python cli.pynot.\avc: Ensures the correct Python environment is used. - Use
read_fileandview_image: Do NOT use additional terminal commands to read output files or display charts. - Built-in exclusions:
c,c++,typespec,swagger,xmlare always excluded automatically.
Other skills for the same job
different authors, same section of the catalogue
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like \"the xlsx in my downloads\") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
Picks random winners from lists, spreadsheets, or Google Sheets for giveaways, raffles, and contests. Ensures fair, unbiased selection with transparency.
Query openFDA API for drugs, devices, adverse events, recalls, regulatory submissions (510k, PMA), substance identification (UNII), for FDA regulatory data analysis and safety research.
MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing. Use when writing MATLAB/Octave scripts for linear algebra, signal processing, image processing, differential equations, optimization, statistics, or creating scientific visualizations. Also use when the user needs help with MATLAB syntax, functions, or wants to convert between MATLAB and Python code. Scripts can be executed with MATLAB or the open-source GNU Octave interpreter.
UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.
Creating interactive data visualisations using d3.js. This skill should be used when creating custom charts, graphs, network diagrams, geographic visualisations, or any complex SVG-based data visualisation that requires fine-grained control over visual elements, transitions, or interactions. Use this for bespoke visualisations beyond standard charting libraries, whether in React, Vue, Svelte, vanilla JavaScript, or any other environment.
Access AlphaFold 200M+ AI-predicted protein structures. Retrieve structures by UniProt ID, download PDB/mmCIF files, analyze confidence metrics (pLDDT, PAE), for drug discovery and structural biology.
How to use it
Take azure/report-apiview-metrics from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.