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name: career-online-presence description: "Use when building or auditing an individual professional's online presence and findability — personal website (Person schema, canonical bio), GitHub portfolio, multi-platform social strategy (LinkedIn content cadence, X, Bluesky, Threads), newsletters (Substack), YouTube, AI people-search visibility (how ChatGPT, Perplexity, Gemini answer 'who is '), and digital-footprint hygiene under employer screening. Includes a mandatory regulated-employee publishing check (finance/FINRA/MNPI). Trigger on - personal website, GitHub profile, online presence, personal brand online, be found by AI, Bluesky, Threads, Substack, newsletter strategy, digital footprint, what does ChatGPT say about me. Part of the career-* skill family; business/brand E-E-A-T lives in seo-authority-builder; e-commerce AI visibility lives in ai-search-optimizer." family: career disambiguation: The public artefacts and their findability — personal site, Person schema, GitHub profile, what search returns. What message those artefacts should carry is career-positioning.

Career Online Presence

Builds the person-as-findable-entity: how a specific professional shows up across their own site, GitHub, social platforms, newsletters, video, and AI people-search — and how their public footprint reads to an employer screening them.

The discoverability stack:

• Canonical layer — your personal website: the one source you control, schema-marked, that everything else points back to.
• Distribution layer — the platforms (LinkedIn, GitHub, Bluesky/Threads/X, Substack, YouTube) where you actually show up.
• Authority-earned-off-site principle — most of the signals that make AI engines and recruiters trust you live off your own domain (mentions, third-party corroboration). You build the canonical home, then earn the off-site signal.

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When NOT to Use

The user actually wants…	Route to
Business / brand entity E-E-A-T, Knowledge Panel, company reputation	seo-authority-builder
Product / page / e-commerce AI-answer visibility (AEO)	ai-search-optimizer
LinkedIn profile copy and content strategy	career-positioning
Long-form drafting voice (the actual writing of a post/article)	content-writer + human-voice-writing
Application documents (CV, cover letter)	career-application-writer

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HARD RULES

1. Read the user profile first. Read ~/.claude/skills/career-coach/references/user-profile.md before any presence plan.
2. Regulated-employee publishing check BEFORE any posting plan. Before recommending any public posting, confirm the user's situation against the employer/regulatory surface: employer social-media / external-comms policy; FINRA Rule 2210 + SEC personal-communications rules if the user is a registered person; MNPI (material non-public information). Never advise posting client names, internal systems, proprietary architecture, performance/return claims, or investment advice; always disclose relevant affiliations. When in doubt → compliance pre-clearance. Full checklist in references/finance-confidentiality.md. This gate runs first and gates every later step.
3. No fabricated credentials or projects. Presence amplifies real work; it never invents a project, a title, or a contribution.
4. Cross-platform consistency. The footprint is screened — titles, dates, and claims across site / LinkedIn / GitHub / CV must agree (cross-check with career-application-writer).
5. Privacy floor. Deliberately separate personal and professional surfaces; be aware of doxxing surface (home address, family, schedule); remember "publish once, findable forever" — assume nothing is truly deletable.
6. Terminology. "Professional development / competency / capability / fluency", never "skill(s)" for the user's growth. (Implementer note: GitHub/LinkedIn UI labels like the "Skills" section are quoted terms of art, not the family's competency usage.)

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1. Personal Website — the Canonical Entity Home

Your site is the one node you fully control. Make it the canonical entity:

• Schema-marked with JSON-LD Person + sameAs linking every profile you own (worked example in references/person-schema.md). This is what AI engines and search read to resolve "who is ".
• Canonical bio — one authoritative bio, reused verbatim across platforms (consistency is itself a trust signal).
• Page model: home/bio, portfolio/work, selected case studies, contact.
• Freshness discipline — stale pages lose AI citations over time (fresh content is cited more often — see market-snapshot-2026-06.md). Update on a realistic cadence rather than building once and abandoning.

2. GitHub Portfolio (technical roles)

• Depth over count: two deployed projects with live URLs and strong READMEs beat ten tutorial clones (recruiter weighting — see market-snapshot-2026-06.md).
• At least one LLM-API project is now an expected signal for many technical roles.
• Pin 6 repos; curate the profile README; keep commit history legible (a recruiter does a quick walkthrough, not a code review).
• The profile is read as a portfolio, not a code archive — front the work you want to be hired for.

3. Multi-Platform Social

• No single X successor — take a portfolio approach: Bluesky skews developer/journalist; Threads has mainstream scale; X retains residual reach (current standings shift fast — see market-snapshot-2026-06.md).
• Pick 1–2 platforms by where your audience actually is; don't spray across all of them.
• Cadence realism: a sustainable rhythm you'll keep beats an ambitious one you'll abandon (the abandoned-feed effect is its own negative signal).
• LinkedIn content mechanics stay in career-positioning (360Brew ranking, the 5 content pillars, Saves/Sends) — this skill covers off-LinkedIn presence; point there for LinkedIn strategy.

4. Long-Form & Video

• Newsletter (e.g. Substack): doubles as distribution and search-indexed long-form that builds entity authority. Route the actual drafting to content-writer (and human-voice-writing for the voice pass) — this skill decides whether/where, not how it's written.
• YouTube / community platforms: a large share of AI-engine citations trace to community platforms (see market-snapshot-2026-06.md), so video and community participation can disproportionately help findability — if sustainable for the user.

5. AI People-Search Findability

The new discoverability question is "what does ChatGPT/Perplexity/Gemini say when someone asks about me?"

• Monthly self-query protocol: query the major answer engines for "who is " and " + "; record what they say and what they get wrong.
• Entity-recognition tracking sheet: track, per engine, whether you're recognized, what sources they cite, and any errors.
• Corrections strategy: fix misattribution by strengthening canonical sources and third-party corroboration (the Person schema, consistent bios, a few authoritative mentions) — entity hygiene over volume posting. You can't out-post a wrong entity graph; you correct the graph.

6. Digital-Footprint Hygiene & Screening

• Employers check public footprints, and dedicated screening tools exist (see market-snapshot-2026-06.md).
• Audit-your-own-footprint protocol: search yourself the way a screener would; review old public posts, tagged content, and forum history; reconcile anything that contradicts your CV/LinkedIn.
• Cleanup + consistency beat volume — a clean, coherent footprint is the goal, not maximal output.

7. The 90-Day Presence Build (tiered by ROI, compliance-gated)

Run HARD RULE 2 first — every step below is gated on the regulated-employee check.

Phase	Focus	Why first
Days 1–30	Canonical site + Person schema; reconcile cross-platform consistency; footprint self-audit	The canonical layer is the foundation everything points to
Days 31–60	Pick 1–2 distribution platforms; GitHub portfolio cleanup (pin 6, READMEs); set a sustainable cadence	Distribution only pays off once the canonical home exists
Days 61–90	Long-form / newsletter if sustainable; first AI people-search self-query baseline; corrections pass	Authority and findability compound after the base is set

Every recommendation in the plan re-checks the compliance gate before it suggests publishing anything.

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Output Artefacts

• Canonical bio + Person/sameAs schema block.
• A 1–2 platform distribution plan with a realistic cadence.
• GitHub portfolio cleanup checklist (tech roles).
• AI people-search tracking sheet + corrections plan.
• A compliance-gated 90-day build.

Anti-Patterns

Anti-Pattern	Why it fails	Correct approach
Posting more as a substitute for entity hygiene	Volume can't fix a wrong entity graph	Strengthen canonical sources + corroboration (§5)
Ignoring the employer comms policy	Compliance breach risk; career-ending in regulated roles	Run HARD RULE 2 + finance-confidentiality.md first
Abandoned-blog / dead-feed effect	A stale presence is a negative signal	Pick a cadence you can actually sustain
Spraying across every platform	Thin, inconsistent presence everywhere	Pick 1–2 where your audience is
Fabricated or inflated projects	Screened against your real footprint; integrity failure	Amplify real work only (HARD RULE 3)
Footprint that contradicts the CV	Screening tools flag the mismatch	Cross-document consistency (HARD RULE 4)