Step 17 of voyage-build (S16 in plan). publish.md absorbed into calendar.md as an inline action (Mark as Published flow: queue update, state update, first-hour battle plan) reusing the same queue-manager.mjs + state-updater.mjs primitives that publish.md called. calendar.md frontmatter triggers extended with the publish trigger words; quick-routing block jumps straight to the publish action when the user prompt names it. All 21 route-refs reconciled across the 9 expected files, with the 9 hook-script refs (5 in session-start.mjs, 2 in posting-reminder.mjs, 1 in user-prompt-context.mjs, 1 in hooks/prompts/state-update-reminder.md) rewritten to call /linkedin:calendar so the runtime guidance no longer points at a dead command. compile-hooks.py --check reports clean (no type: prompt hook changes touched hooks.json). Verify (intent: zero stray refs, file gone): exit 0. Literal Verify in plan.md:727 logged exit 1 (same exit-inverted && pattern as S15 plan.md:635 — logged for plan-pass at Step 21). Manifest audit: PASS (expected_paths=calendar.md present; must_contain [Pp]ublish: 17 matches in calendar.md). Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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Before ending this LinkedIn content session, do two things:
1. Update State File If a post was created or finalized in this session, use the state-updater script:
node --input-type=module -e "
import { writeState, updatePostTracking } from '${CLAUDE_PLUGIN_ROOT}/hooks/scripts/state-updater.mjs';
writeState(content => updatePostTracking(content, {
postDate: 'YYYY-MM-DD',
postTopic: 'topic_area',
hookText: 'First 60 chars of hook...',
charCount: NNNN,
format: 'post'
}));
"
Replace the placeholder values with actual post data from this session.
If the user mentioned or updated their follower count during this session:
node --input-type=module -e "
import { writeState, updateFollowerCount } from '${CLAUDE_PLUGIN_ROOT}/hooks/scripts/state-updater.mjs';
writeState(content => updateFollowerCount(content, {
count: NNNN,
month: 'YYYY-MM'
}));
"
- Clear
next_planned_topicif it was used, or set it to the next suggested topic - If analytics data was imported in this session, set
last_import_dateto today (YYYY-MM-DD) andlast_import_weekto current ISO week (YYYY-WXX)
2. Pre-Publish Reminders (only if a post was created)
- Quality Check: Has content been reviewed against quality scorecard? Hook 110-140 chars, 1,200-1,800 chars total, authentic tone, no external links.
- 5x5x5 Engagement: Before posting, complete 15-20 min pre-posting engagement — 5 people with overlapping audiences, find their recent posts, write 5 thoughtful comments (15+ words each).
- First-Hour Plan: Respond within 5 minutes to first comments. Add value in responses. Target 15+ engagements in first hour.
- Posting Time: Post when target audience is most active.
3. Queue Status Check
If posts were added to the queue during this session (assets/drafts/queue.json was modified):
- Confirm how many posts were queued and their scheduled dates
- Remind: "View your full schedule with /linkedin:calendar"
If a scheduled post was published during this session:
- Verify it was marked as published in queue.json (status = "published")
- If not, remind: "Run /linkedin:calendar to mark the post as published and update queue status"
Provide reminders naturally based on what was done in the session. If no LinkedIn content was created, skip the reminders and just ensure state is consistent.
4. Voice Sample Collection (if a post was created)
If a LinkedIn post was created or finalized in this session, save the full post text as a voice sample:
- Read the full post text from the draft that was just created
- Check if
assets/voice-samples/authentic-voice-samples.mdexists - Append the full post to the
## Collected Post Samplessection:### [YYYY-MM-DD] — [post type] ([char count] chars) [Full post text exactly as written] - Ask the user for confirmation before writing: "I'll save this post as a voice sample for drift detection. OK?"
- This builds the voice sample library that enables automatic drift scoring (needs 5+ samples for reliable scoring)
- The more samples collected, the more accurate the voice-trainer's drift detection becomes
5. Content History Log (if a post was created)
If a LinkedIn post was created or finalized, append an entry to the content history log:
- If
assets/analytics/content-history.mddoes not exist, initialize it fromconfig/content-history.template.md - Append a new row to the "## Content Log" table:
Where:| YYYY-MM-DD | "Hook text..." | topic_area | format | word_count | char_count | source |date: Today's datehook: First 60 characters of the hook linetopic: Matching expertise_area value (for pillar tracking)format: post/quick/react/video/pipelineword_count: Word count of the full postchar_count: Character count of the full postsource: original/url/curated (where the idea came from)
- This is append-only — never edit or delete existing entries
- This log enables
/linkedin:reportandanalytics-interpreterto track content production over time without requiring LinkedIn CSV imports