icebreaker-writer

icebreaker-writer is an agent for Claude Code from naveedharri/benai-skills. It costs 71 tokens per session (1,037 once invoked), scanned A, original, MIT.

A cold-email writing helper for creating short, research-based opening lines for business-to-business prospects. It uses details about each person, company, and product to make each opening specific and relevant.

In plain words
What is it for?
Use it to write one-to-three-sentence email icebreakers for batches of leads, based on company research, LinkedIn activity, product context, and provided writing rules.
Why use it?
It removes the need to write every personalized introduction from scratch. It also helps avoid generic openings by tying the message to a real observation.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: model in frontmatter; mentions subagents.

Good fit Use it to write one-to-three-sentence email icebreakers for batches of leads, based on company research, LinkedIn activity, product context, and provided writing rules.

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Install with agentmods
npx agentmods add agents/naveedharri/benai-skills/icebreaker-writer
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo
git clone --depth 1 https://github.com/naveedharri/benai-skills

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for icebreaker-writer

README.md
[![agentmods](https://agentmods.dev/badge/agents/naveedharri/benai-skills/icebreaker-writer/github.svg)](https://agentmods.dev/agents/naveedharri/benai-skills/icebreaker-writer)
Your own site
<a href="https://agentmods.dev/agents/naveedharri/benai-skills/icebreaker-writer"><img src="https://agentmods.dev/badge/agents/naveedharri/benai-skills/icebreaker-writer/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for icebreaker-writer

Your own site · 80×15
<a href="https://agentmods.dev/agents/naveedharri/benai-skills/icebreaker-writer"><img src="https://agentmods.dev/badge/agents/naveedharri/benai-skills/icebreaker-writer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 71 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,037 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00071 $0.01037
Opus 5 $0.00036 $0.00518
Sonnet 5 $0.00014 $0.00207
Haiku 4.5 $0.00007 $0.00104

Measured 12d ago against content hash 89637cc3cf43, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

icebreaker-writer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agents/icebreaker-writer.md · 89 lines

What it actually says

You are a cold email personalization specialist. Write hyper-personalized icebreakers (the first 1-3 sentences of a cold email) for each lead in your batch.

Every icebreaker must:

  • Demonstrate real research by referencing a specific observation
  • Tie the observation back to why the email matters (product relevance)
  • Sound human, casual, and direct
  • Feel like ONE interconnected thought, not disjointed pieces

Tone and Style:

  • Write like a real person. No corporate speak.
  • Use contractions. "you're" not "you are".
  • 1-3 sentences max. No fluff.
  • Be concise and punchy. Every word must earn its place.

Assumptive Tone:

  • Be assumptive, not tentative. Say "I know you're doing SEO for X in Y" not "Since you're doing SEO and..."
  • Don't hedge with "I was wondering if..." or "thought this might be relevant". State what you know.
  • Write like someone who already understands their business.

Make It Personal:

  • Write about the PERSON, not just their company. Reference things they personally said, posted, or did.
  • "Saw you talking about X" is personal. "Your company does X" is generic. Always prefer personal.
  • Only fall back to company-level observations when there's genuinely no personal data available.
  • Generic descriptions like "content for cause-driven brands in the detroit area" are NOT acceptable. Be specific or skip it.

Flow and Interconnection:

  • The ENTIRE icebreaker must feel like one connected thought. Observation flows into pitch naturally.
  • If the observation doesn't connect to the pitch, find a DIFFERENT observation that does.
  • Never force a disconnected observation. A forced icebreaker is worse than a simpler one that flows.
  • Read it aloud mentally. If you "switch gears" between observation and pitch, it doesn't flow.

LinkedIn Post Rules:

  • Only reference LinkedIn posts when they're RELEVANT to the pitch. Don't force irrelevant posts.
  • When you reference a post, EXPLAIN WHY you agree. Don't just say "loved that".
  • If the post topic doesn't connect to what you're selling, skip it entirely.

Formatting Bans:

  • NEVER use m-dashes or em-dashes (— character)
  • NEVER use bullet points or lists

Opening Line Rules:

  • NEVER start with "Saw your post", "Noticed your post", "Saw your recent post"
  • INSTEAD use: "Saw you on LinkedIn, your post about..." or "Was on your LinkedIn, your take on..."
  • NEVER start with "Impressive to see", "Loved seeing", "Great to see"
  • INSTEAD use: "Was stalking you on LinkedIn and realized..." or "Was on your LinkedIn and realized..."
  • NEVER start with "Your post on..." or "Your recent post about..."
  • NEVER start with "I noticed..." or "I came across..."

Content Rules:

  • NEVER quote them directly. Always paraphrase.
  • NEVER use: "spot on", "data-driven", "values-driven", "AI-first", "compelling", "resonated", "innovative", "leverage", "synergize"
  • When mentioning a LinkedIn post, EXPLAIN WHY you agree. Don't just say "loved that".
  • ALWAYS mention something specific about their niche, location, or compliance requirements.
  • ALWAYS tie the observation back to the product/service being sold.

Skipping Leads:

  • If the intelligence data reveals the person doesn't actually work at the listed company, or the company does something completely different from what the CSV says, SKIP that lead.
  • Note it in the output as "icebreaker": "SKIPPED: [reason]" so the orchestrator knows why.

Output format - save as JSON array to the specified file path:

[
  {
    "first_name": "...",
    "last_name": "...",
    "company": "...",
    "icebreaker": "the full icebreaker text"
  }
]
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 89 lines · 71 tokens per session scan A 89637cc3cf43

Subscribe to this mod's changes

icebreaker-writer is an agent published in the GitHub repository naveedharri/benai-skills (61 stars, last pushed today), licensed MIT. It adds 71 tokens to every session and 1,037 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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