quality
Compiles a code quality report based on progress.md frontmatter and repository baseline analysis.
Install
mkdir -p .claude/skills/quality && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/12043" && unzip -o skill.zip -d .claude/skills/quality && rm skill.zipInstalls to .claude/skills/quality
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Generate a code quality report for a pipeline project by reading quality frontmatter from progress.md and optionally running fresh analysis.Key capabilities
- →Read quality frontmatter from `progress.md`
- →Run fresh complexity analysis against the repository baseline
- →Perform fresh per-file analysis if the project branch exists
- →Generate a code quality report in markdown format
- →Attach the quality report to the work item
How it works
The skill extracts quality metrics from `progress.md`, optionally runs fresh code analysis, and compiles the data into a markdown report that is then attached to the work item.
Inputs & outputs
When to use quality
- →Generate quality report for pipeline
- →Review milestone complexity metrics
- →Verify code quality against project baseline
About this skill
Quality
You generate a code quality report for a pipeline project by reading the pipeline_quality_* frontmatter from progress.md, optionally running fresh analysis against the repo baseline, and attaching a quality report to the work item.
Inputs
wcp_get_artifact($ARGUMENTS, "progress.md")— quality frontmatter from Stage 5 implementation milestones- The current repository — for running fresh baseline and per-file analysis
- The conventions file — for Complexity Analysis tool configuration
Before You Start
- Locate the conventions file in the current repo root — look for
CLAUDE.md,AGENTS.md, orCONVENTIONS.md(use the first one found). Read it in full. From the## Pipeline Configurationsection, extract Repository Details (default branch, branch prefix, etc.), and look for a Complexity Analysis section. - Read progress.md:
wcp_get_artifact($ARGUMENTS, "progress.md")
If progress.md does not exist, STOP:
"No progress artifact found for
$ARGUMENTS. Run Stage 5 implementation first."
Step-by-Step Procedure
1. Read Quality Frontmatter
wcp_get_artifact($ARGUMENTS, "progress.md") — extract YAML frontmatter. Parse all pipeline_quality_* fields:
Per-milestone fields (pattern: pipeline_quality_mN_*):
pipeline_quality_mN_flog_avgpipeline_quality_mN_flog_maxpipeline_quality_mN_flog_max_methodpipeline_quality_mN_files_analyzed
Project summary fields (written by /create-pr):
pipeline_quality_flog_avgpipeline_quality_repo_baseline_flog_avgpipeline_quality_deltapipeline_quality_verdictpipeline_quality_files_analyzed
If no pipeline_quality_* fields exist in the frontmatter, STOP with a helpful message:
"No quality data found in progress.md for
$ARGUMENTS. Quality metrics are captured during Stage 5 implementation when the conventions file has a Complexity Analysis section.To add quality data to an existing project, a future
/backfill-qualityskill (ROAD-20 v2) will support checking out old branches and running analysis retroactively."
2. Run Current Repo Baseline
If the conventions file has a Complexity Analysis section, run the repo baseline command for a fresh comparison:
<repo-baseline-command>
Parse the output to extract the current repo-wide flog/method average. Store as current_baseline.
If the command fails or the section doesn't exist, use the stored pipeline_quality_repo_baseline_flog_avg from frontmatter (if available) or —.
3. Fresh Per-File Analysis (Optional)
Check if the project branch still exists:
git branch --list '<branch-prefix>$ARGUMENTS'
If the branch exists:
- Check out the branch:
git checkout <branch-prefix>$ARGUMENTS - Get all pipeline-touched files:
git diff --name-only origin/<default-branch>...<branch-prefix>$ARGUMENTS -- '<file-glob>'(exclude spec/) - Run the score command on each file to get fresh per-file scores
- Run the per-file command on files with the highest scores to identify current hotspot methods
- Check out the previous branch:
git checkout -
If the branch does not exist (already merged/deleted), note this in the report and rely solely on frontmatter data.
Failure handling: If any command fails, log a warning and continue with frontmatter data only. Never fail the report because of a stale branch.
4. Write Quality Report
Attach the quality report to the work item:
wcp_attach(
id=$ARGUMENTS,
type="quality",
title="Quality Report",
filename="quality.md",
content="[quality report]"
)
Use the following template for the report content:
# Code Quality Report — $ARGUMENTS
> Generated: <current date/time>
> Tool: [tool name from Pipeline Configuration, or from frontmatter context]
> Hotspot threshold: [threshold from Pipeline Configuration, or "unknown"]
## Quality Scorecard
| Metric | Value |
|--------|-------|
| **Project flog avg** | [from frontmatter or fresh analysis] |
| **Repo baseline avg** | [current_baseline or stored baseline] |
| **Delta** | [delta] |
| **Verdict** | [verdict] |
| **Total files analyzed** | [files_analyzed] |
## Per-Milestone Breakdown
| Milestone | Flog Avg | Flog Max | Max Method | Files |
|-----------|----------|----------|------------|-------|
| M1 | [m1_flog_avg] | [m1_flog_max] | [m1_flog_max_method] | [m1_files_analyzed] |
| M2 | ... | ... | ... | ... |
[One row per milestone with quality data]
## Hotspots
[Top 5 methods above the hotspot threshold, from fresh analysis if available, otherwise from per-milestone flog_max data]
| Score | Method | Source |
|-------|--------|--------|
| [score] | [ClassName#method_name] | [file path or milestone] |
[If no methods above threshold: "No methods above the hotspot threshold of [threshold]."]
## Baseline Context
| Metric | Value |
|--------|-------|
| **Stored baseline** (at PR time) | [pipeline_quality_repo_baseline_flog_avg] |
| **Current baseline** | [current_baseline or "—"] |
| **Baseline drift** | [current - stored, or "—"] |
> Baseline drift shows how the repo average has changed since the PR was created. A rising baseline means overall repo complexity is increasing.
## Data Quality Notes
- [Note whether data is from frontmatter only or includes fresh analysis]
- [Note if project branch was available for fresh analysis]
- [Note any milestones missing quality data]
- [Note if baseline was live or stored]
5. Handle Missing Data
- If a per-milestone field is missing, display
—in the table - If project summary fields are missing (no
/create-prrun yet), compute from per-milestone data if possible - If the branch is gone, note "Fresh analysis unavailable — branch merged/deleted" and use frontmatter only
- Use
—for any metric that cannot be computed
6. Post Completion Comment
Add a comment to the work item summarizing the quality report:
wcp_comment(
id=$ARGUMENTS,
author="pipeline/quality",
body="Quality report attached as quality.md — [verdict summary]"
)
What NOT To Do
- Do not modify any project documents. Only attach
quality.mdto the WCP work item. - Do not modify source code. This is a read-only analysis tool.
- Do not fabricate scores. Use
—for missing data. - Do not run pipeline stages. This is a standalone reporting tool.
- Do not leave the repo on a different branch. Always
git checkout -after analysis.
When You're Done
Tell the user:
- The quality report has been attached to
$ARGUMENTSasquality.md - Summarize key metrics: project flog avg, delta from baseline, verdict
- Highlight any hotspots above threshold
- Note data quality limitations (frontmatter vs fresh, branch availability)
When not to use it
- →If `progress.md` does not exist
- →If no `pipeline_quality_*` fields exist in the frontmatter
Limitations
- →Does not modify any project documents or source code
- →Does not fabricate scores, uses `,` for missing data
- →Does not run pipeline stages, acts as a standalone reporting tool
How it compares
This skill generates a structured quality report by combining stored metrics with fresh analysis, providing a consolidated view of code quality, unlike manually collecting and presenting metrics.
Compared to similar skills
quality side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| quality (this skill) | 0 | 5mo | Review | Intermediate |
| optimize-report | 0 | 3mo | Review | Beginner |
| github-code-review | 13 | 2mo | Review | Advanced |
| reviewing-nextjs-16-patterns | 11 | 8mo | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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