feat(linkedin-studio): honest newsletter distribution + profile-SEO + outreach pipeline

Step 17 (Wave 4 S4) of the audit remediation. Applies research/03 §D5 + the
two S2 residual fixes folded in. No new commands/agents (counts stay 27/19).

Newsletter (commands/newsletter.md): new "Distribution channel" section after
Step 10 teaching the HONEST native-newsletter mechanics — bypasses organic feed
ranking via ONE deduplicated notification per subscriber per edition (NOT a
three-touchpoint blast); the mass invite fires once → ~1-2K follower floor
(wait until you can spend it); realistic cold-start 0-100 subs months 1-3;
discloses non-export / no-canonical / no-read-analytics / per-subscriber decay;
explicit below-vs-above-floor decision rule. Sourced to research/03 D5.

Profile (commands/profile.md): new "Profile SEO" section — headline as the
highest-weight search field + a per-section keyword-target table
(headline/about/experience/skills/featured), consistency-over-stuffing rule.

Outreach (commands/outreach.md): Step 8c persists the pipeline board to tracked
state via the new recordOutreachContact mutation (mirrors Step 16's
recordFirstHourPlan): additive last_outreach_date/outreach_active scalars + a
non-R-initial ## Outreach Pipeline section in state-updater.mjs +
config/state-file.template.md + --record-outreach CLI branch. +7 tests
(state-updater 26→33, full hook suite 83→90).

Residual 1 (growth-playbook:216): 9:16 "distribution boost" → 4:5/1:1 guidance
(9:16 mobile-only opt-in; "immersive distribution" = uncorroborated heuristic).
Residual 2 (video-strategy-guide:300): "3-second test determines 70% retention"
→ "front-load value for muted autoplay" (three-second hook is folklore, not a
LinkedIn signal).

Verify: grep checks 1-5 pass; test-runner.sh exit 0 (stat-consistency green);
state-updater 33/33. [skip-docs] — tre-doc + version bump deferred to Step 21.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

plugins/linkedin-studio/commands/profile.md

@@ -38,6 +38,40 @@ LinkedIn's 150B parameter foundation model evaluates five criteria:
 | **Network** | Connected to professionals in this space? | MEDIUM - social proof |
 | **Engagement Patterns** | Do you comment on posts about your topics? | MEDIUM - active participation |
 
+## Profile SEO — your profile is also a search surface
+
+Topic-relevance ranking (above) governs **content distribution**. Separately,
+your profile is **indexed by LinkedIn search** — when someone searches a topic, a
+role, or a skill, LinkedIn keyword-matches profile fields to decide who surfaces.
+The two reinforce each other: the same keywords that tell the relevance model
+what you're expert in are the ones that make you findable. Optimize for both.
+
+**The headline is your highest-weight search field.** It is keyword-matched, shown
+in every search result and connection suggestion, and renders under your name
+across the site — so it does the most SEO work per character. Lead with the plain
+words people actually search (the role, the domain, the audience), not a clever
+tagline. "AI Advisor · public-sector AI governance · Microsoft Copilot" is more
+findable than "Turning chaos into clarity ✨".
+
+**Per-section keyword targets** (place the terms a searcher would type, in the
+words they'd type them — not synonyms only you use):
+
+| Section | Keyword target | Why it ranks |
+|---------|----------------|--------------|
+| **Headline** | 3–4 primary topic terms + audience + role | Highest-weight search field; always visible |
+| **About** | Same primary terms, front-loaded in the first 2–3 lines, then 5–8 supporting terms naturally across the body | Indexed for search; first lines double as the relevance model's expertise signal |
+| **Experience (titles + body)** | The searchable job title (not an internal-only label) + 2–3 domain terms per role | Job titles are weighted in search; an internal title nobody searches is invisible |
+| **Skills** | Your top 3 skills = your 3 core content topics, exact-match to common search terms | Matched directly against recruiter/search skill filters |
+| **Featured** | Posts whose titles carry your topic terms | Reinforces the topic association for both search and relevance |
+
+**Rule of thumb:** pick your 3–5 core topics once, then make the *same* terms
+appear — in the searcher's own words — in the headline, the About opener, the
+skills, and your recent post topics. Keyword **consistency across sections**
+beats keyword **stuffing in any one section**: LinkedIn rewards a coherent
+expertise signal, and a profile crammed with unrelated terms reads as noise to
+both the search index and the relevance model. Avoid buzzwords nobody searches
+("thought leader", "guru", "ninja") — they cost a keyword slot and return nothing.
+
 ## Profile Audit Walkthrough
 
 Guide the user through each section using AskUserQuestion for interactive feedback.