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npx skills add paramchoudhary/resumeskills --skill cold-email-writer
Write personalized cold outreach emails to hiring managers and founders — specific, human, not a pitch deck
npx skills add paramchoudhary/resumeskills --skill cold-email-writer
Use this skill when the user wants to:
Cold emails fail because they sound like cover letters. The goal is to sound like a smart person who genuinely noticed something specific about the company — not a candidate broadcasting their credentials.
The email should feel like: A colleague mentioning something interesting they read, not a sales pitch.
Simple. No clickbait. No role title. Just a name.
Start with what genuinely pulled the candidate in. Must be specific to this company — not a generic compliment.
What makes a good hook:
What makes a bad hook:
If the candidate is in a different country from the company, disclose it early and casually:
If the role lists more years than the candidate has, acknowledge it briefly and redirect:
Current role → relevant past → one or two projects. Keep it contextual, not a list.
Rules:
Bridge between their background and the specific role. Should feel like an observation, not a claim.
Or more specific:
One line. No elaboration.
End with low-pressure, confident energy. Not desperate, not corporate.
Avoid:
Before writing the email, gather:
If the user provides a JD but no company website, ask for it or fetch it before writing.
Longer is fine if every sentence earns its place. Cut anything that could apply to any company.
Always wrap the final email in a plain code block for clean copy-paste:
Too confident: ❌ "I would be an exceptional addition to your team" ❌ "My background uniquely positions me for this role" ✅ "I feel like I'd be a strong fit" — states a belief, doesn't claim certainty
Too humble: ❌ "I know I may not have all the experience you're looking for, but..." ❌ "I'm just reaching out on the off chance..." ✅ Acknowledge gaps directly and move on — don't apologize
Too long: ❌ Three paragraphs listing every achievement ✅ One paragraph on background, one on the connection
Too generic: ❌ Opening with "I am writing to express my interest in..." ✅ Opening with what specifically pulled them to this company
No research: ❌ "I love your product and mission" ✅ "The 5% stat — only 5% of a $25B market online — doesn't feel like a feature gap, it feels like an entire industry that hasn't digitised"
A bit about me: I currently work at [Company], [one line on what the company does],
where I [what they actually do there — not a job title]. Before that I worked
with teams in [region], mostly around [relevant domain].
On the side I've been building [Project] ([link if applicable]) — [one line: what
it is and one proof point like "got to paying clients" or "20K downloads"].I think you're looking for [what the role actually wants] — that's the kind of
work I've been doing, and honestly I feel like I'd be a strong fit.My stack maps naturally to yours — [specific tech overlap]. But more than the
stack, it's the [domain/problem] that I'm genuinely interested in.More about me: [portfolio URL]I'm currently at [Company] and open to what's next. I think my experience lends
nicely to what you're building — so I think we'd both get something out of a
conversation.
[First Name]
[email]Subject: Quick intro — [Name]
Hi [Name],
[Email body]
[First Name]
[email]Subject: Quick intro — Sarah Chen
Hi Marcus,
I just came across Meridian and spent more time on your site than I planned.
What pulled me in was the framing around your data infrastructure — you're not
just building an LLM layer on top of existing records, you're rethinking how
clinical data flows through the system in the first place. That's a harder
problem and a more interesting one.
I'm based in India, flagging that upfront. Happy to figure out the rest if
there's a real fit.
I currently work at Lune, a London-based climate intelligence company, where I
build event-driven data pipelines and agentic AI workflows for emissions
compliance — regulated, data-intensive systems where reliability isn't optional.
I also built Memos, a RAG system from scratch: hybrid retrieval, reranking,
ChromaDB, FastAPI. And InframetAI, an SDK for LLM cost and latency
observability that came out of seeing what breaks when the data layer isn't
designed around how models actually work.
I think you're looking for engineers who've actually built AI systems end to
end, not just wrapped APIs. That's the work I've been doing.
More about me: yourportfolio.com/about
I'm currently at Lune and open to what's next. I think my experience maps
closely to what you're building — so I think we'd both get something out of
a conversation.
Sarah
sarah@email.com