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Analysis window: recent runs (last ~1 hour of activity captured in this run — GitHub's Artifacts API only exposes non-expired artifacts, and the most recent runs dominate the sample). 20 workflows had artifacts across 20 distinct runs, totaling 99 artifacts, ~~135 MB combined.
Workflow Name
Artifacts Count
Total Size
Avg Size
Latest Run
Status
Daily Cli Tools Tester
8
9.3 MB
1.2 MB
2026-08-02 06:18 UTC
Active
Contribution Check
7
9.2 MB
1.3 MB
2026-08-02 05:54 UTC
Active
Schema Consistency Checker
7
9.2 MB
1.3 MB
2026-08-02 06:23 UTC
Active
Multi-Device Docs Tester
2
9.2 MB
4.6 MB
2026-08-02 06:24 UTC
Active
CLI Version Checker
8
9.1 MB
1.1 MB
2026-08-02 06:25 UTC
Active
Static Analysis Report
8
9.0 MB
1.1 MB
2026-08-02 06:19 UTC
Active
Daily Sub-Agent Model Resolution Audit
3
8.9 MB
3.0 MB
2026-08-02 06:25 UTC
Active
Issue Arborist
7
8.9 MB
1.3 MB
2026-08-02 06:19 UTC
Active
Daily Windows Terminal Integration Builder
7
8.8 MB
1.3 MB
2026-08-02 05:49 UTC
Active
Dictation Prompt Generator
5
8.7 MB
1.7 MB
2026-08-02 06:24 UTC
Active
GitHub Remote MCP Authentication Test
6
8.6 MB
1.4 MB
2026-08-02 06:23 UTC
Active
The Great Escapi
8
8.6 MB
1.1 MB
2026-08-02 05:48 UTC
Active
PR Sous Chef
5
8.5 MB
1.7 MB
2026-08-02 06:24 UTC
Active
AI Moderator
6
8.4 MB
1.4 MB
2026-08-02 05:57 UTC
Active
ESLint Refiner
1
8.3 MB
8.3 MB
2026-08-02 06:10 UTC
Active
Artifacts Usage Report
1
8.3 MB
8.3 MB
2026-08-02 06:23 UTC
Active
Daily Container Image Security Scan
1
8.3 MB
8.3 MB
2026-08-02 06:20 UTC
Active
Workflow Health Manager - Meta-Orchestrator
6
1.4 MB
243 KB
2026-08-02 05:43 UTC
Active
Safe Output Health Monitor
3
8.3 KB
2.8 KB
2026-08-02 05:41 UTC
Active
Agentic Maintenance
1
1.1 KB
1.1 KB
2026-08-02 05:41 UTC
Active
Methodology & data limitations
Data source: GET /repos/github/gh-aw/actions/artifacts (single page, most recent 99 non-expired artifacts returned by the API at query time — GitHub does not retain historical/expired artifact metadata beyond expiry, so this reflects a live snapshot rather than a true rolling 30-day history).
Each artifact was mapped to its originating run via run.workflow_run.id, then each run was resolved to its workflow name via GET /repos/github/gh-aw/actions/runs/{id}.
All 20 workflows observed in this snapshot have zero expired artifacts, so all are marked Active. A true 30-day trend requires either enabling artifact-retention audit logging or running this report periodically and diffing snapshots, since expired artifacts disappear from the API.
Sizes shown are size_in_bytes converted to MB/KB (1024-based).
Insights & Recommendations
Most artifacts generated: Daily Cli Tools Tester, CLI Version Checker, and Static Analysis Report (8 artifacts each) — these run frequently (daily/hourly cadence) and produce multiple small artifacts (logs, agent output, usage stats) per run.
Largest storage consumers: Several single-artifact workflows (ESLint Refiner, Artifacts Usage Report itself, Daily Container Image Security Scan) each upload one ~8.3 MB artifact, likely full container-build or docker-build cache artifacts rather than logs.
Most efficient: Safe Output Health Monitor and Agentic Maintenance produce tiny (KB-scale) artifacts — good practice, minimal storage footprint.
Trend: This snapshot only captures a short recent window because GitHub's Artifacts API surfaces only non-expired artifacts; most gh-aw lock workflows use short retention windows, so long-term trend analysis isn't possible from a single snapshot.
Recommendations:
For workflows uploading large (~8 MB) single artifacts (docker build caches, container scan results), consider shortening retention-days further or excluding these from artifact upload if not needed for debugging.
For high-count/low-size artifact workflows (Daily Cli Tools Tester, CLI Version Checker, Static Analysis Report), consider consolidating multiple small artifacts (e.g., agent, usage, aic-usage-cache) into a single combined archive per run to reduce artifact-count overhead.
To get true 30-day trends, schedule this report to run periodically and persist historical stats (e.g., in a tracking issue/discussion) rather than relying on a single point-in-time query, since expired artifacts are not retrievable retroactively.
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Analysis window: recent runs (last ~1 hour of activity captured in this run — GitHub's Artifacts API only exposes non-expired artifacts, and the most recent runs dominate the sample). 20 workflows had artifacts across 20 distinct runs, totaling 99 artifacts, ~~135 MB combined.
Methodology & data limitations
GET /repos/github/gh-aw/actions/artifacts(single page, most recent 99 non-expired artifacts returned by the API at query time — GitHub does not retain historical/expired artifact metadata beyond expiry, so this reflects a live snapshot rather than a true rolling 30-day history).run.workflow_run.id, then each run was resolved to its workflow name viaGET /repos/github/gh-aw/actions/runs/{id}.size_in_bytesconverted to MB/KB (1024-based).Insights & Recommendations
gh-awlock workflows use short retention windows, so long-term trend analysis isn't possible from a single snapshot.Recommendations:
retention-daysfurther or excluding these from artifact upload if not needed for debugging.agent,usage,aic-usage-cache) into a single combined archive per run to reduce artifact-count overhead.All reactions