agency-docs-updater

name	agency-docs-updater
description	End-to-end pipeline for publishing Claude Code lab meetings. Accepts optional args: date (YYYYMMDD, "yesterday", "today") and lab number (e.g. "04"). Examples: "yesterday 04", "20260420 05", "04" (today, lab 04), "" (today, auto-detect lab).

Agency Docs Updater

Execute ALL steps automatically in sequence. Only pause if a step fails and cannot be recovered. Read references/learnings.md before starting for known pitfalls.

Configuration: paths are read from .env in the skill root (see .env.example). Defaults work for the standard setup. Key env vars: VAULT_DIR, DOCS_SITE_DIR, YOUTUBE_UPLOADER_DIR, PRESENTATIONS_DIR, SKILLS_REPO_DIR, SKILLS_LOCAL_DIR, ZOOM_CREDENTIALS_DIR, GITHUB_REPO, SITE_DOMAIN.

Dependencies (verify these exist before running):

• zoom — Zoom recording download (scripts/zoom_meetings.py)
• fathom — Fathom video fallback (scripts/download_video.py)
• nano-banana — thumbnail overlay generation (scripts/generate_image.sh)
• calendar-sync — local-only, calendar event sync (sync.sh)
• youtube-uploader — video processing, upload, and YouTube API auth

Step 0: Parse Arguments & Load Config

Load .env from skill root. Then split args by whitespace:

• 8-digit token (YYYYMMDD) → DATE
• "yesterday" → DATE = $(date -v-1d +%Y%m%d)
• "today" or missing → DATE = $(date +%Y%m%d)
• 2-digit token (NN) or lab-NN → LAB_FILTER
• slug token (e.g. ai-design, claude-code) → LAB_SLUG (overrides env; default claude-code)

Expand env vars for paths used in subsequent steps:

VAULT_DIR="${VAULT_DIR:-$HOME/Brains/brain}"
DOCS_SITE_DIR="${DOCS_SITE_DIR:-$HOME/Sites/agency-docs}"
YOUTUBE_UPLOADER_DIR="${YOUTUBE_UPLOADER_DIR:-$HOME/ai_projects/youtube-uploader}"
SKILLS_REPO_DIR="${SKILLS_REPO_DIR:-$HOME/ai_projects/claude-skills}"
SKILLS_LOCAL_DIR="${SKILLS_LOCAL_DIR:-$HOME/.claude/skills}"
ZOOM_CREDENTIALS_DIR="${ZOOM_CREDENTIALS_DIR:-$HOME/.zoom_credentials}"
PRESENTATIONS_DIR="${PRESENTATIONS_DIR:-$HOME/ai_projects/claude-code-lab}"
GITHUB_REPO="${GITHUB_REPO:-glebis/agency-docs}"
SITE_DOMAIN="${SITE_DOMAIN:-agency-lab.glebkalinin.com}"
LAB_SLUG="${LAB_SLUG:-claude-code}"   # e.g. ai-design for the AI Design Lab
LAB_TITLE="${LAB_TITLE:-$(echo $LAB_SLUG | tr '-' ' ' | awk '{for(i=1;i<=NF;i++) $i=toupper(substr($i,1,1)) substr($i,2)}1' | sed 's/^Ai /AI /')}"  # "Claude Code", "AI Design"

Step 0a: Preflight (recommended)

Run the preflight doctor to catch the three common mid-pipeline failures up front (missing youtube-uploader Python deps, missing Playwright/chromium, dead Groq key):

bash ${SKILLS_LOCAL_DIR}/agency-docs-updater/scripts/preflight.sh

Hard blockers (deps/Playwright) exit non-zero with the exact fix command — run it, then re-run preflight. A dead Groq key is a soft warning: the LLM metadata step will 401, so plan to supply title/description/tags manually (build a VideoConfig and call upload.py directly, then set the thumbnail and playlist separately).

Step 1: Find Fathom Transcript

If LAB_FILTER is set: ${VAULT_DIR}/${DATE}-${LAB_SLUG}-lab-${LAB_FILTER}.md If empty: glob ${VAULT_DIR}/${DATE}-${LAB_SLUG}-lab-*.md (pick most recent by mtime). If nothing matches and no explicit slug was given, fall back to ${VAULT_DIR}/${DATE}-*-lab-*.md and derive LAB_SLUG from the match.

If missing: run ${SKILLS_LOCAL_DIR}/calendar-sync/sync.sh, re-check, stop if still missing.

Extract from YAML frontmatter and store:

• FATHOM_FILE, SHARE_URL, MEETING_TITLE, DATE, LAB_NUMBER
• VIDEO_NAME = ${DATE}-${LAB_SLUG}-lab-${LAB_NUMBER}
• TRANSCRIPT_LANG = auto-detect from first ~50 lines (Cyrillic ratio > 0.3 → ru, else en)

Resolve the lab layout FIRST — paths, page URLs, and playlist names differ per lab. Never build them by hand; resolve through the registry:

python3 ${SKILLS_LOCAL_DIR}/agency-docs-updater/scripts/lab_layout.py ${LAB_SLUG} --lab ${LAB_NUMBER} --meeting ${MEETING_NUMBER} --json
# → meetings_dir (relative to DOCS_SITE_DIR), page_url, playlist, lang, thumbnail_style,
#   preserve_placeholder_frontmatter, registered

The registry is labs.json in the skill root (claude-code legacy layout, GDD RU goal-driven-design-ru, GDD EN). update_meeting_doc.py and rebuild_aggregations.py resolve through it automatically. Unregistered slugs fall back to the legacy {slug}-internal-{lab} scheme with a warning — add new labs to labs.json, don't improvise paths. Use playlist for Step 4b (search the existing playlist list by this exact name before creating), page_url for Step 4b/8, lang for summary/MDX language, and honor preserve_placeholder_frontmatter (GDD placeholders carry curated toolkit: frontmatter — merge, never overwrite).

Determine MEETING_NUMBER: check existing MDX files in ${DOCS_SITE_DIR}/content/docs/${LAB_SLUG}-internal-${LAB_NUMBER}/meetings/ for a placeholder with today's date. If found, use that number. Otherwise, check file content sizes to find the next empty slot. Store as zero-padded two-digit string (e.g. 04). This variable is used in Steps 3b, 4b, 5, 6, and 8.

Step 2: Download Video

Skip if ${VAULT_DIR}/${VIDEO_NAME}.mp4 exists and is > 1MB.

Note: Zoom recordings may take ~15 minutes to process after a meeting ends. If the Zoom API returns no recordings, wait and retry before falling back to Fathom.

Primary — Zoom:

python3 ${SKILLS_REPO_DIR}/zoom/scripts/zoom_meetings.py recordings \
  --start ${DATE:0:4}-${DATE:4:2}-${DATE:6:2} \
  --end $(date -j -v+1d -f %Y%m%d ${DATE} +%Y-%m-%d) \
  --show-downloads 2>&1

Find the MP4 URL, then:

TOK=$(python3 -c "import json,pathlib; print(json.load(open(pathlib.Path('${ZOOM_CREDENTIALS_DIR}')/'oauth_token.json'))['access_token'])")
curl -L -H "Authorization: Bearer ${TOK}" -o ${VAULT_DIR}/${VIDEO_NAME}.mp4 "${MP4_DOWNLOAD_URL}"

Fallback — Fathom (if no Zoom recording):

cd ${VAULT_DIR} && python3 ${SKILLS_LOCAL_DIR}/fathom/scripts/download_video.py \
  "${SHARE_URL}" --output-name "${VIDEO_NAME}"

Step 3: Upload to YouTube

Step 3-pre: Trim leading silence

Zoom auto-recordings start at meeting open and often begin with minutes of dead air. Before uploading:

bash ${SKILLS_LOCAL_DIR}/agency-docs-updater/scripts/trim_leading_silence.sh ${VAULT_DIR}/${VIDEO_NAME}.mp4
# If it prints "trim: wrote …trimmed.mp4", upload the trimmed file instead of the original.

The script only trims when the file STARTS in silence >10 s, keeps 2 s of lead-in, refuses cuts >20 min, and stream-copies (no re-encode). "no leading silence detected" → use the original.

Smarter cut via transcript (preferred when a timestamped transcript exists — Fathom JSON or Zoom VTT; avoid the merged publication .md, its block timestamps are coarse):

python3 ${SKILLS_LOCAL_DIR}/agency-docs-updater/scripts/detect_lesson_start.py <fathom.json|zoom.vtt> --json
# → {"lesson_start_s": 21.0, "lesson_phrase": "всем привет", "presentation_open_s": 915.0, ...}

It finds (a) the lesson-opening phrase («всем привет», «добро пожаловать», «давайте начинать», "let's start"…) and (b) the presentation-opening moment («открою презентацию», "share my screen"…). Use them as:

• Trim point: max(silence_end, lesson_start_s − 5) — keep the greeting, cut the dead air before it. Sanity-check against the silence result; if the two disagree wildly, inspect before cutting.
• YouTube chapters in the description: 0:00 Начало / MM:SS Презентация (from presentation_open_s, minus the trim offset).

If neither phrase is found, fall back to the plain silence trim.

Tech-difficulty spans. The same detector emits tech_check_spans — screen-share fumbling («видно презентацию?», «меня слышно?», «перешарю», «одну секундочку» рядом со словами презентация/экран). These are CANDIDATES: read each span's context lines first; a genuine question-and-answer about visibility is cuttable, a rhetorical «секундочку» mid-explanation is not. To cut approved spans:

python3 ${SKILLS_LOCAL_DIR}/agency-docs-updater/scripts/cut_spans.py video.mp4 \
  --remove 1245-1270 --remove 781-821        # seconds, from tech_check_spans

cut_spans.py re-encodes (frame-accurate; ~realtime for talking-head 1080p), merges/clamps spans, and refuses to remove >15% of total duration. Cutting shifts everything after each span — compute YouTube chapter timestamps AFTER all cuts. For a single ≤30 s hiccup consider skipping the cut: a full re-encode of a 2 h video may not be worth it.

cd ${YOUTUBE_UPLOADER_DIR} && \
python3 process_video.py \
  --video ${VAULT_DIR}/${VIDEO_NAME}.mp4 \
  --fathom-transcript ${FATHOM_FILE} \
  --title "${MEETING_TITLE}" \
  --upload

Run with run_in_background: true (10-30 min). On failure: --resume-from upload.

Extract YOUTUBE_URL from stdout (✓ YouTube video: ...) or processed/metadata/${VIDEO_NAME}.json. Extract VIDEO_ID from the URL (the part after ?v= or last path segment).

Step 3a: Verify Upload (REQUIRED)

After extracting VIDEO_ID, verify the video actually exists on YouTube before proceeding. Videos can silently fail processing or get auto-deleted by YouTube's content review.

cd ${YOUTUBE_UPLOADER_DIR} && PYTHONPATH=. python3 -c "
from auth import get_authenticated_service
import sys, time

youtube = get_authenticated_service()
video_id = '${VIDEO_ID}'

# Poll up to 5 minutes for video to become available
for attempt in range(10):
    resp = youtube.videos().list(part='status,processingDetails', id=video_id).execute()
    if not resp['items']:
        if attempt < 9:
            print(f'Video not yet available (attempt {attempt+1}/10), waiting 30s...')
            time.sleep(30)
            continue
        print(f'FATAL: Video {video_id} not found after 5 minutes. Upload may have failed.')
        sys.exit(1)

    status = resp['items'][0]['status']
    processing = resp['items'][0].get('processingDetails', {})
    upload_status = status.get('uploadStatus', 'unknown')
    privacy = status.get('privacyStatus', 'unknown')
    rejection = status.get('rejectionReason', None)

    print(f'Upload status: {upload_status}, Privacy: {privacy}')
    if rejection:
        print(f'REJECTED: {rejection}')
        sys.exit(1)
    if upload_status in ('processed', 'uploaded'):
        print(f'✓ Video {video_id} verified OK')
        sys.exit(0)
    if upload_status == 'failed':
        print(f'FATAL: Upload failed — {status.get(\"failureReason\", \"unknown\")}')
        sys.exit(1)

    print(f'Status: {upload_status}, waiting 30s...')
    time.sleep(30)

print('FATAL: Video not ready after 5 minutes')
sys.exit(1)
"

If verification fails: delete the failed video metadata (rm processed/metadata/${VIDEO_NAME}.json), re-upload with --resume-from upload, and re-verify. Do NOT proceed to MDX or thumbnail steps with an unverified VIDEO_ID.

Start Step 4 in parallel — summary doesn't depend on YouTube URL.

Step 3b: Lab-Style Thumbnail (REQUIRED)

Always run this step — it replaces the generic thumbnail from process_video.py with the branded lab template. The generic thumbnail is NOT acceptable for publishing.

Prerequisites: VIDEO_ID must be known (wait for Step 3 to complete if needed).

Follow references/thumbnail-guide.md for the full workflow:

1. Generate Nano Banana overlay image (topic-specific prompt from the guide's prompt patterns)
2. Read/inspect raw image to confirm background color, then recolor lines to orange (#e85d04)
3. Write a temporary HTML file (e.g. /tmp/lab-meeting-${MEETING_NUMBER}.html) based on ${YOUTUBE_UPLOADER_DIR}/templates/images/lab-meeting.html — update meeting number, topic hero text, bullet descriptions, date. Do not edit the original template in-place.
4. Render with Playwright at 1280×720 → ${YOUTUBE_UPLOADER_DIR}/processed/thumbnails/${VIDEO_NAME}.jpg
5. Read/inspect the rendered thumbnail to verify layout before uploading
6. Upload to YouTube: use VIDEO_ID extracted from Step 3

Do NOT skip this step or rely on the process_video.py thumbnail.

Step 4: Generate Fact-Checked Summary

Read ${FATHOM_FILE}. Generate a structured summary in ${TRANSCRIPT_LANG}:

• ## section headers, bullet points, code examples where relevant
• Technical terms in English (MCP, Skills, Claude Code, etc.)
• Exclude personal scheduling details
• Exclude operator/pipeline notes: recording source, trimming or cutting, silence/preamble removal, remuxing or re-encoding, transcript synchronization, upload retries, and other production mechanics belong only in the internal Pipeline Report — never in the published summary or meeting page
• Verify product, company, and person names against authoritative project context or explicit user corrections before publishing; do not trust ASR/LLM normalization for proper nouns
• Sanitize for MDX: escape <, >, and bare { characters that would break MDX compilation

Fact-check Claude Code feature claims using claude-code-guide subagent (if available; skip fact-checking if the agent is not accessible). Save corrected summary to scratchpad as summary.md.

Step 4b: Update YouTube Metadata

After both Step 3 and Step 4 complete. VIDEO_ID, MEETING_NUMBER, and LAB_NUMBER must all be determined before this step. Read references/youtube-api.md for description format and API snippets.

Generate YouTube description from the summary. Use the language-appropriate template:

• If TRANSCRIPT_LANG=en: English labels ("In this video:", "Course materials and session notes:")
• If TRANSCRIPT_LANG=ru: Russian labels ("В этом видео:", "Материалы и конспект занятия:")

Do NOT mix languages in a single description.

Meeting page URL: https://${SITE_DOMAIN}/${LAB_SLUG}-lab-${LAB_NUMBER}/meetings/${MEETING_NUMBER}

Update title, description, tags via YouTube API, then add video to playlist "${LAB_TITLE} Lab ${LAB_NUMBER}" (auto-created if it does not exist).

Step 5: Generate MDX

LAB_SLUG=${LAB_SLUG} python3 ${SKILLS_LOCAL_DIR}/agency-docs-updater/scripts/update_meeting_doc.py \
  ${FATHOM_FILE} "${YOUTUBE_URL}" ${SCRATCHPAD}/summary.md

Before running: check if a placeholder MDX already exists for today's date (grep -l in meetings/). If so, use -n ${MEETING_NUMBER} --update to target it.

After running:

1. Strip appended Marp content (everything after summary's closing --- before <!-- _class: lead -->) — MDX breaks on HTML comments (<!-- -->), unescaped <, and bare { characters
2. Check for presentation file: look in ${PRESENTATIONS_DIR}/presentations/lab-${LAB_NUMBER}/ (set PRESENTATIONS_DIR per lab; the ai-design lab keeps decks elsewhere — skip if unset for the slug) and ${PRESENTATIONS_DIR}/lesson-generator/ for files matching ${DATE}. If found, copy to ${DOCS_SITE_DIR}/public/${DATE}-${LAB_SLUG}-lab-${LAB_NUMBER}.html and add link in MDX
3. Replace frontmatter placeholders ([Название встречи], [Краткое описание встречи], [Дата встречи])
4. If TRANSCRIPT_LANG=en, rewrite the MDX entirely with English labels — the script defaults to Russian and the translation fallback produces broken mixed-language output
5. Verify: bash ${SKILLS_LOCAL_DIR}/agency-docs-updater/scripts/safe_build.sh (wraps npm run build; auto-clears a corrupt .next cache and retries once on the reading 'hash' / ENOSPC error)
6. Search the generated MDX for operator/pipeline notes (recording provenance, edit/cut details, encoding, transcript synchronization, upload mechanics) and remove them before publication
7. Search the MDX, public transcript, YouTube metadata, and thumbnail copy for known ASR variants of corrected proper nouns; use the canonical spelling consistently across every public surface

Step 6: Commit and Push

Only stage pipeline files — never git add .:

cd ${DOCS_SITE_DIR}
git fetch origin main
BEHIND=$(git rev-list --count HEAD..origin/main)
if [ "$BEHIND" -gt 0 ]; then
  git stash push -m "agency-docs-updater: temp stash"
  git pull --rebase origin main
  git stash pop || true
fi
git add content/docs/${LAB_SLUG}-internal-${LAB_NUMBER}/meetings/${MEETING_NUMBER}.mdx
# Only stage presentation HTML if it was copied
[ -f public/${DATE}-${LAB_SLUG}-lab-${LAB_NUMBER}.html ] && git add public/${DATE}-${LAB_SLUG}-lab-${LAB_NUMBER}.html
git commit -m "Add ${LAB_TITLE} Lab ${LAB_NUMBER} Meeting ${MEETING_NUMBER}"
git push

Store COMMIT_HASH=$(git rev-parse HEAD) for Step 7.

Step 7: Wait for Vercel Deploy

TIMEOUT=300; ELAPSED=0
until [ "$(gh api repos/${GITHUB_REPO}/commits/${COMMIT_HASH}/status --jq '.state' 2>/dev/null || echo 'pending')" != "pending" ]; do
  sleep 15; ELAPSED=$((ELAPSED+15))
  [ "$ELAPSED" -ge "$TIMEOUT" ] && echo "Deploy timeout after ${TIMEOUT}s" && break
done
DEPLOY_STATE=$(gh api repos/${GITHUB_REPO}/commits/${COMMIT_HASH}/status --jq '.state')
echo "Deploy state: ${DEPLOY_STATE}"

Run with run_in_background: true. If state is failure or error: check Vercel logs (vercel logs), fix locally, re-push, restart this step.

Step 8: Verify in Browser

Open https://${SITE_DOMAIN}/${LAB_SLUG}-lab-${LAB_NUMBER}/meetings/${MEETING_NUMBER} in a browser (via chrome automation tools or manually). Verify YouTube embed is visible. If not: check VIDEO_ID, wait for YouTube processing, or re-upload.

Step 9: Rebuild Site-Wide Aggregations

After the new meeting is committed (Step 6), regenerate the three site-wide aggregations from all meetings so the new one is reflected: the database (meetings index), the glossary, and the global library of links.

python3 ${SKILLS_LOCAL_DIR}/agency-docs-updater/scripts/rebuild_aggregations.py

The script reads the same .env paths and writes (paths configurable via AGG_* env vars):

• content/docs/database.mdx + public/data/meetings.json — index of every meeting
• content/docs/glossary.mdx (definitions persisted in .agency-glossary.json)
• content/docs/library.mdx — deduplicated external links across all meetings

Handle new glossary terms: the script prints → N NEW term(s) need definitions for terms it has never seen. For each, write a one-line definition into ${DOCS_SITE_DIR}/.agency-glossary.json (keep technical terms in English; match the page language otherwise), then re-run the script so the glossary MDX regenerates with the definitions. Leave already-defined terms untouched — the store is the source of truth.

Then: bash ${SKILLS_LOCAL_DIR}/agency-docs-updater/scripts/safe_build.sh to confirm the generated MDX compiles (auto-recovers from a corrupt .next cache), stage the changed aggregation files (the three MDX pages, public/data/meetings.json, and .agency-glossary.json — never git add .), and commit:

git add content/docs/database.mdx content/docs/glossary.mdx content/docs/library.mdx \
        public/data/meetings.json .agency-glossary.json
git commit -m "Rebuild aggregations after Lab ${LAB_NUMBER} Meeting ${MEETING_NUMBER}"
git push

This commit can be folded into Step 6's commit if you prefer a single push; either way it must land before re-running Step 7's deploy wait.

Pipeline Report

After completion, report: Fathom path, video path, YouTube URL, MDX path, commit hash, deploy status, embed verification, and the aggregation rebuild (meeting count, any new glossary terms defined).

Related: fan-out maintenance workflows

For repo-wide jobs across all past meetings — auditing every page for broken embeds/MDX defects, or backfilling/repairing incomplete meetings — see references/workflows.md. Those are fan-out dynamic workflows (one agent per meeting), run on demand, separate from this single-meeting pipeline.