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course-update-recon

Testing & Quality
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Characterize a slow / stuck course-update worker on dashboard.wikiedu.org or outreachdashboard.wmflabs.org. Use this skill when asked to investigate why a course update is taking unusually long, hung, or running for many hours, or to estimate the scale-of-work of an in-flight update. Pure HTTP recon against public APIs — never SSH into prod.

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Source SKILL.md: https://github.com/WikiEducationFoundation/WikiEduDashboard/blob/HEAD/.claude/skills/course-update-recon/SKILL.md

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Course-update recon

Workflow for characterizing a slow or stuck course update without ever touching prod. The goal is a per-axis estimate of the work-in-flight (or work-just-completed) so we can predict runtime and pick a fix.

Hard rule: never SSH to peony-web, peony-database, peony-sidekiq, dashboard.wikiedu.org, or any other prod host.* All recon is via public dashboard JSON endpoints + public Wikimedia APIs. If you need something only available inside the prod app, ask the user to run a one-liner and paste the result back.

Step 1 — Resolve course id → slug

The numeric id is what the user usually has; the public JSON endpoints key on slug. The /find_course/<id> endpoint redirects from id to the canonical course URL — read the Location: header to get the slug:

curl -sSI -A "WikiEdu-Dashboard-Recon/1.0 (sage@wikiedu.org)" \
  https://outreachdashboard.wmflabs.org/find_course/<ID> | grep -i location
# Location: https://outreachdashboard.wmflabs.org/courses/<SLUG>

For Wiki Ed Dashboard courses use https://dashboard.wikiedu.org/find_course/<ID>. Slugs may contain ', : etc. — URL-encode before hitting the JSON endpoints.

Step 2 — Pull course.json + users.json

SLUG_ENC="...url-encoded slug..."
HOST=https://outreachdashboard.wmflabs.org   # or dashboard.wikiedu.org

curl -sS "$HOST/courses/$SLUG_ENC/course.json"
curl -sS "$HOST/courses/$SLUG_ENC/users.json"

From course.json, note: start, end, home_wiki, wikis, updates.average_delay, and updates.last_update (start_time, end_time, processed, reprocessed). The last_update.end_time is the last completed update — if a worker is currently running, it won't appear here.

From users.json, extract users[].username (filter by role if you want to exclude instructors/staff — role 0 = student, 1 = instructor).

Step 3 — Bucket contributions along the three cost axes

Per the 2026-04-24 benchmark (.claude/plans/benchmark_notes-2026-04-24.md):

AxisPer-unit costDriver
Non-wikidata (enwiki etc.) ns=0 revs~4 s/revReferenceCounter (2× per rev) + Lift Wing
Wikidata revs (any ns)~0.2 s/revReplica + WikidataDiffAnalyzer (batched)
Commons uploads0.5 s (healthy) – 10 s (observed stalled) per uploadUploadImporter serial thumburl + usage_count

Use benchmarks/probe_course_contributions.rb — it runs the recon against list=usercontribs for ns=0 on each non-wikidata wiki, list=usercontribs (all ns) on wikidata, and list=allimages on Commons, then projects total runtime from the per-axis costs.

SLUG='Polskojęzyczna_Wikipedia/Wikiprojekt_Nauki_medyczne' \
  ruby benchmarks/probe_course_contributions.rb

Required env: SLUG (course slug). Optional: HOST (default outreachdashboard.wmflabs.org; switch to dashboard.wikiedu.org for Wiki Ed courses), WINDOW_START / WINDOW_END to narrow the probe window, PER_USER_CAP to raise the per-user pagination cap (default 5000), USERS_LIMIT to spot-check a subset.

Step 4 — Sanity-check projection vs. observed runtime

Compare projected wall time to:

  • The user's reported runtime ("update has been running 9 hours")
  • updates.average_delay (seconds between completed updates) — if the projection is way under average_delay, an external factor (Toolforge service down, Lift Wing slow, etc.) is likely the culprit, not the course's edit volume.

If projected « observed: it's a service-availability problem, not a scale problem. If projected ≈ observed: it's pure scale and a reference-counter / Lift Wing batch fix would help.

Step 5 — Report

Summarize for the user:

  • Course shape (home_wiki, # users, window, last completed update)
  • Per-axis edit counts in the window
  • Projected runtime range (low/high)
  • Whether projected runtime explains observed runtime, or whether a different bottleneck is implicated (and which one to investigate next — Toolforge tool status, Lift Wing latency, etc.)

Reference files

  • benchmarks/probe_course_contributions.rb — generic per-axis probe; drives off SLUG env var
  • benchmarks/cuwprofile_http.rb — per-HTTP-call profiler for a real UpdateCourseStats run (dev DB only, not prod recon); supports MODE=cold|warm|incremental|cold+warm
  • .claude/plans/benchmark_notes-2026-04-24.md — cost model derivation + per-endpoint timings
  • .claude/plans/plan_course_update_perf_regression-2026-04-24.md — loose ends from the 35819 investigation (UploadImporter, sidekiq-status TTL, etc.)