Install
openclaw skills install cm-linkedin-profile-optimizerAudit and rewrite LinkedIn profiles for recruiter visibility, inbound leads, and category authority. Diagnoses headline, About, Experience, Skills, Featured,...
openclaw skills install cm-linkedin-profile-optimizerAudit and rewrite LinkedIn profiles for three outcomes: (1) showing up in recruiter and buyer searches, (2) converting profile views into inbound DMs, and (3) building category authority that compounds. Acts as a profile strategist who has reviewed thousands of profiles for engineers, PMs, designers, sales reps, founders, and marketers.
Invoke this skill when a profile is underperforming or being prepared for a job search, fundraise, or B2B outbound campaign.
Basic invocation:
Audit my LinkedIn profile: [paste headline + About + last 2 roles] Rewrite my LinkedIn headline — I'm a backend engineer targeting senior roles at Stripe-tier companies My profile gets views but no DMs, what's broken?
With context:
I'm a founder raising a seed round, optimize my profile for VC searches I'm a SaaS AE, rewrite my About to attract inbound buyers not recruiters Help me rank for "Kubernetes platform engineer" — recruiters can't find me
The agent diagnoses against a fixed framework, rewrites every section, and produces a 30-day activity plan.
The agent scores eight surfaces. A profile must hit all eight to compound — fixing only one creates a leaky funnel.
| Surface | What It Does | Pass Criteria |
|---|---|---|
| Banner | First visual; signals seriousness | Not the default blue. Includes value prop or proof (logos, tagline, headshot at conference). |
| Headline (220 chars) | The single biggest ranking and click factor — appears in search, comments, DMs | Outcome + role + niche + 1-2 keywords recruiters Boolean-search. Not just job title. |
| About (2,600 chars) | Where the visitor decides to act | Hook in line 1, credibility in lines 2-3 (above the "see more" fold), proof, CTA. |
| Featured | Above-the-fold proof | 3-4 items: best post, case study, podcast, lead magnet. Refresh quarterly. |
| Experience | Where recruiters/ATS scan keywords; where buyers verify legitimacy | STAR bullets with metrics, not job descriptions. Top 3 roles get the most depth. |
| Skills | Drives "People also viewed" matching, recruiter filters | Top 3 pinned = the 3 keywords you want to rank for. 50+ endorsements on the top 3. |
| Recommendations | Social proof recruiters and buyers explicitly read | Minimum 5 recent (within 18 months). Mix of manager, peer, customer, report. |
| Activity | Drives all-LinkedIn distribution; SSI; profile views | Active in the last 7 days. Comments > posts > shares for first 30 days. |
The agent produces a per-surface score (0-2: missing / weak / strong) and ranks fixes by ROI.
SSI is LinkedIn's internal ranking signal (sales-nav.linkedin.com/sales/ssi). It's scored 0-100 across four pillars of 25 each. A score above 70 is the working threshold for inbound. Above 80 unlocks meaningful reach.
| Pillar | What Moves It | Tactic |
|---|---|---|
| Establish your professional brand | Profile completeness, posts published, long-form articles | Hit "All-Star" status; publish 1 long-form per quarter; pin Featured. |
| Find the right people | Sales Navigator searches, saved leads, advanced filters used | Even without Sales Nav: do 5 saved-search-style queries per week, view 10 profiles in target niche per day. |
| Engage with insights | Posts, comments, reactions, shares, message replies | Comment thoughtfully on 5 posts/day from people 1-2 levels above you. |
| Build relationships | Connections at decision-maker level, acceptance rate, message reply rate | Connect with 10 targeted people/week with personalized notes. Maintain >50% acceptance. |
Quick wins (raise SSI 10-15 points in two weeks):
LinkedIn search is closer to ATS keyword matching than Google — recurring exact phrases win. Recruiters use Boolean: "product manager" AND ("fintech" OR "payments") AND "B2B" NOT "junior".
Keyword extraction process:
Snowflake, dbt, Figma), frameworks (Jobs-to-be-done, OKRs), domains (B2B SaaS, marketplaces, series A), and outcomes (MRR growth, 0-to-1, migration).Density rules:
Recruiter Boolean fluency — what they actually type:
("software engineer" OR "backend engineer") AND ("Go" OR "Golang") AND "Kubernetes" AND ("staff" OR "principal")
("product manager" OR "product lead") AND "fintech" AND ("0-1" OR "0 to 1") NOT (intern OR junior OR associate)
("VP marketing" OR "head of marketing") AND ("B2B SaaS") AND ("series A" OR "seed")
Audit your profile by literally pasting these into LinkedIn search and checking whether you appear in the first 10 results for your target string.
The headline is 220 characters, weighted heaviest by search, and shown next to your name on every comment. The default — your job title — wastes the slot.
Formula: Outcome | Role + Niche | Keywords | Proof or Hook
Use |, →, or • as separators. Avoid emoji noise (one is fine; five is spam).
Five before/after rewrites:
WEAK: Senior Software Engineer at Acme Corp
STRONG: I help fintechs ship secure payment APIs | Senior Backend Engineer | Go, Kubernetes, PCI-DSS | ex-Stripe
WHY: Adds outcome ("ship secure payment APIs"), niche ("fintechs"), three Boolean keywords,
and a proof anchor. Same person, 8x more searchable.
WEAK: Product Manager
STRONG: 0-to-1 PM for B2B SaaS | I take products from first 10 customers to first $1M ARR | ex-Notion, ex-Linear
WHY: "0-to-1" and "$1M ARR" are exact phrases founders search. Names former employers
that act as social proof and keyword anchors.
WEAK: Marketing professional with 8 years of experience
STRONG: Demand Gen leader for B2B SaaS | Built pipeline engines from $0 to $40M ARR at 3 startups | ABM, PLG, Paid
WHY: Replaces vague "8 years experience" with quantified outcomes ($0-$40M, 3 startups).
Three keyword anchors at the end (ABM, PLG, Paid) catch all common Boolean searches.
WEAK: Founder & CEO at Stealth Startup
STRONG: Founder, building [Company] — modern observability for AI agents | YC W26 | hiring eng #2-#5
WHY: "Stealth" tells nobody anything. Specific category ("observability for AI agents")
attracts both press and recruiters. "YC W26" is a Boolean magnet for VCs. "Hiring"
signals the profile owner is reachable.
WEAK: Account Executive | Top performer | Quota crusher
STRONG: Enterprise AE for DevTools | Closed $4.2M ARR last 4 quarters at [Company] | I sell to platform & infra teams
WHY: "Top performer" is unverifiable noise. "$4.2M ARR" + "platform & infra teams" gives
the buyer ICP information and recruiters a quota datapoint they can filter on.
WEAK: UX Designer | Passionate about user-centered design
STRONG: Senior Product Designer for B2B SaaS | I ship interfaces for AI/data products | ex-Figma, ex-Retool
WHY: "Passionate about user-centered design" is true of literally every designer.
Replacing it with a domain ("AI/data products") and proof anchors makes the profile
findable for the 5 search strings hiring managers actually use.
The About section has 2,600 characters but only the first ~220 show before the "see more" fold on mobile. That's where the visitor decides whether to expand.
Structure: Hook → Credibility → Proof → CTA
Worked example — engineering manager:
WEAK (current):
"Experienced engineering manager passionate about building high-performing teams and shipping
quality software. I love mentoring engineers and working on challenging problems. Always open
to new opportunities."
STRONG (rewrite):
"I run engineering teams that ship reliable distributed systems — payments, search, identity —
at the scale where small bugs become $1M incidents.
Currently EM at [Company] (Series C, fintech). Previously led 14 engineers at Stripe across
the Issuing platform. Before that, founded a YC-backed dev tools company (acquired 2023).
What I've actually shipped:
• Cut p99 latency 480ms → 90ms on the core payments path serving 8B requests/year
• Grew an 8-person team to 22 across two timezones with <5% regrettable attrition over 3 years
• Owned the migration from monolith to 6-service architecture (zero downtime, 14-month rollout)
• Designed the on-call rotation now used across 60+ engineers in the org
I write occasionally about platform engineering, on-call culture, and how to interview senior
engineers — pinned in Featured below.
Open to: Director / Sr EM roles at Series B-D companies in payments, infra, or developer tools.
DM me — I respond within 24h."
WHY:
• Hook is a specific category claim ("payments, search, identity") not vague passion.
• Credibility hits two famous brands (Stripe, YC) within the first 200 chars — above the fold.
• Proof bullets all have numbers. "Led a team" becomes "8 → 22 with <5% attrition."
• CTA is concrete: target seniority, target stage, target domain, response SLA.
Most profiles paste job descriptions: "Responsible for managing a team and shipping features." This signals nothing. Rewrite every bullet as STAR (Situation → Task → Action → Result), prioritizing the Result.
Bullet template: [Verb] [scope/system] [resulting in] [metric over baseline] [in timeframe].
Before/after:
WEAK: "Led the migration of legacy services to microservices."
STRONG: "Led 14-month migration of monolithic Rails app (1.2M LOC, 80 engineers) to 6-service
architecture; reduced deploy time from 45min to 4min and unblocked 3 product teams
to ship independently."
WEAK: "Improved sales pipeline."
STRONG: "Rebuilt outbound motion (sequencing, ICP scoring, AE/SDR pairing); pipeline grew 3.4x
in 6 months, win rate moved from 14% to 22%, ramp time for new AEs cut from 9mo to 5mo."
WEAK: "Designed mobile app onboarding."
STRONG: "Redesigned onboarding flow for 2.3M MAU mobile app after 6-week research sprint
(38 user interviews); D7 retention +18%, completion rate 41% → 67%, shipped in 2 weeks
with zero regression."
Bullet rules:
LinkedIn lets you list 50 skills but only the top 3 are pinned and visible in the snapshot. Those three drive recruiter filter matching and the "People also viewed" graph.
Top-3 pinning strategy:
Product Management, not Product Strategy & Vision Leadership).Endorsement game:
Skills to remove:
Microsoft Word, Teamwork).The biggest mistake is starting with posts. Posts from a cold profile reach <100 people. Comments on big-account posts reach thousands and bring real profile views.
Days 1-10: Comment-only phase
Days 11-20: Comment + react + DM
Days 21-30: Post cadence
What "good comment" looks like:
Recommendations are the #1 social-proof signal recruiters actually read. Most profiles have 0-2. Five recent ones is a moat.
Outreach template (give first):
Subject: A recommendation I drafted for you
Hey [Name],
I've been meaning to write you a LinkedIn recommendation. I drafted this — feel free to edit
or scrap it. No reply needed.
> [3-4 sentence specific recommendation: a project you collaborated on, a metric, what made
> them unusually good. Avoid generic adjectives.]
If you're up for returning the favor, I'm currently repositioning toward [target role/niche].
The angles that would help me most are [skill 1], [skill 2], and [outcome you want validated].
Zero pressure either way.
— [Your name]
Send to 8-10 people. Realistic conversion: 4-6 reciprocate. Mix of manager, peer, direct report, and customer/vendor produces the strongest profile.
Once the profile is rewritten, recruiters won't all find you organically — accelerate by reaching out to them directly.
Recruiter search filters:
Title: "technical recruiter" OR "talent partner", Industry: [your target], Company: [target list].Hi [Name] — saw you hire [role] at [Company]. I'm a [your role] with [headline outcome].
Open to chatting if [Company] is hiring. Profile has the rest. Either way, happy to connect.
Each role type has a different "what good looks like." Optimize accordingly:
| Role | Headline Anchor | About Body Focus | Featured |
|---|---|---|---|
| Engineer | Stack + scale ("Go + Kubernetes at 8B req/year") | Systems shipped, incidents owned, migrations led — not "passionate about clean code" | Tech blog post, talk video, GitHub link |
| PM | Domain + stage ("0-to-1 PM for B2B fintech") | Outcomes shipped, NOT features; metrics that moved (NPS, retention, ARR) | Case study, product launch press, podcast |
| Designer | Domain + medium ("Product designer for AI/data") | Before-after screenshots, research depth, ship cadence | Dribbble/portfolio, case study, screenshot |
| Sales (AE/CSM) | Quota + ICP ("Closed $4.2M ARR at DevTools to platform teams") | Quotas hit, deal sizes, ICP, methodology (MEDDIC, Sandler) | Customer logo wall, podcast, webinar |
| Founder | Category + stage ("Building observability for AI agents, YC W26") | Why now, why you, traction, hiring | Pitch deck (light), press, hiring page |
| Marketer | Function + stage ("Demand Gen leader, $0→$40M ARR at 3 startups") | Pipeline created, channels owned, frameworks (PLG, ABM, SEO) | Case study, podcast, lead magnet |
Anti-patterns by role:
BEFORE
─────────────────────────────────────────────────────────────────
Headline: Founder & CEO at Stealth | Entrepreneur | Building cool things
Banner: Default blue
About: "Serial entrepreneur passionate about technology and innovation.
Currently building something exciting in stealth mode. Previously
worked at multiple startups. Always open to chat with smart people."
Skills: Leadership, Entrepreneurship, Strategy
Featured: (empty)
Activity: Last post 11 months ago
AFTER
─────────────────────────────────────────────────────────────────
Headline: Founder, Lumen — observability for AI agents | YC W26 | Previously eng lead
on Datadog APM | Hiring eng #2-#4
Banner: Product screenshot + tagline "See what your agents actually do"
+ small headshot, top-right.
About:
"Most LLM apps fail in production not because the model is wrong, but because nobody
can see what the agent did. Lumen is observability built for AI agents — traces, eval
deltas, and prompt diffs in one timeline.
I'm Petro, founder of Lumen (YC W26). Before this I led the APM ingest team at Datadog
for 4 years (we 6x'd ingest throughput on the same hardware). Before that, founded a
small dev tools company acquired by GitLab in 2021.
What we've shipped in 4 months:
• 38 design partners across YC W25/W26 batches
• Trace volume: 14M agent steps/day
• $42K MRR, growing 31% MoM
• Open-source SDK: 1.4K GitHub stars
Hiring:
→ Founding engineer #2 (TS / Go, distributed systems)
→ Founding designer
→ Developer advocate
I post weekly about: agent reliability, eval design, why traditional APM breaks for
LLMs. Pinned posts in Featured below.
Email: petro@lumen.dev — I reply within 12h."
Skills (top 3): Observability • AI Infrastructure • Distributed Systems
Featured: Lumen launch post (HN), YC video, hiring page, top blog post
Activity: 3 posts/week, 5 comments/day on AI infra & YC accounts
WHY THIS WORKS
─────────────────────────────────────────────────────────────────
- Headline names the category ("observability for AI agents") that VCs and journalists
search for, anchors social proof (YC, Datadog), signals reachability (hiring).
- About hook is a specific contrarian claim, not a feel-good intro.
- Above-the-fold text mentions YC, Datadog, GitLab — three keyword and credibility hits.
- Bullets are quantified (MRR, MoM growth, GitHub stars) — investors can underwrite the
profile in 30 seconds.
- CTA is unambiguous: hiring three roles, email response SLA stated.
BEFORE
Headline: Software Engineer at Acme | Coding enthusiast
About: "I'm a software engineer who loves building things. Skilled in many
technologies. Open to opportunities."
AFTER
Headline: Backend Engineer for high-throughput systems | Go, Postgres, Kafka
| Building payments at Acme (ex-Square) | Open to Senior/Staff roles
About:
"I build backend systems where small bugs become large incidents — payments, ledgers,
fraud. I optimize for correctness first, throughput second, and developer ergonomics
third.
Currently Backend Engineer at Acme (Series C fintech). Previously 4 years at Square on
the Issuing platform. CS @ University of [X], 2018.
Recent work I'm proud of:
• Rewrote the payment-retry pipeline (Go, Kafka): cut duplicate charges 92%, recovered
$1.4M/year in failed-then-succeeded transactions
• Built the idempotency layer used by 11 internal services; zero double-write incidents
in the 18 months since launch
• Reduced p99 latency on the core auth-charge path from 480ms → 90ms (profiling +
connection pool tuning + a Postgres index rewrite)
• Wrote and maintain the on-call runbooks for our 8-engineer payments team
Stack I use day-to-day: Go, PostgreSQL, Kafka, Redis, Kubernetes, Datadog, Terraform.
Looking for: Senior or Staff Backend roles at Series B+ fintech, payments, or infra
companies. Remote (US/EU timezones) or hybrid in NYC.
DM me here, or petro@email.com — I reply within 24h."
The agent produces: