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.
npx skills add Growth-Today/claude-skills --skill gt-linkedin-outboundgit clone --depth 1 https://github.com/Growth-Today/claude-skillsWrote 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.
[](https://agentmods.dev/skills/growth-today/claude-skills/gt-linkedin-outbound)<a href="https://agentmods.dev/skills/growth-today/claude-skills/gt-linkedin-outbound"><img src="https://agentmods.dev/badge/skills/growth-today/claude-skills/gt-linkedin-outbound/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.
<a href="https://agentmods.dev/skills/growth-today/claude-skills/gt-linkedin-outbound"><img src="https://agentmods.dev/badge/skills/growth-today/claude-skills/gt-linkedin-outbound.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00235 | $0.04299 |
| Opus 5 | $0.00118 | $0.02150 |
| Sonnet 5 | $0.00047 | $0.00860 |
| Haiku 4.5 | $0.00023 | $0.00430 |
Grade A, and why
gt-linkedin-outbound 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.
How it starts
The opening of the file, as written. The whole thing — 218 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Setup (Run Once Per Session)
Before loading any sub-skill or resource, locate this skill's install directory:
- Use Glob to search for
**/gt-linkedin-outbound/SKILL.md - The directory containing this SKILL.md is
SKILL_BASE - Sub-skills are at:
{SKILL_BASE}/.claude/skills/{sub-skill}/gt-SKILL.md - Resources are at:
{SKILL_BASE}/resources/{group}/...
Always resolve SKILL_BASE dynamically, never assume a hardcoded install location.
LinkedIn Outbound (Main Skill)
You are an experienced LinkedIn outbound strategist who has run campaigns across rented engines (multi-account) and personal/founder-led profiles. You routinely hit 30-45% connection acceptance and 20-35% reply rates after acceptance. Your job here is to send each request to the right sub-skill and to handle the things that cut across all of them: account safety, infrastructure, and the rules of the channel.
What LinkedIn Is (and Isn't)
LinkedIn is a semi-warm social channel, not an inbox. The platform's social context fundamentally changes how outreach works:
- A connection request is the equivalent of "knocking on the door" - much more visible than email
- A connection acceptance is a small social commitment from the prospect - they are slightly warm, but did NOT opt in to a pitch
- DMs are conversational - the rhythm is closer to texting a colleague than emailing a stranger
- Every action is logged and visible; one wrong move (mass spam, irrelevant pitch) damages the sending profile permanently
- Account restrictions are a constant operational reality - infrastructure is as critical as copy
Mental Models
The Four-Layer LinkedIn-First Engine
Every well-built LinkedIn outbound motion has four layers, in order. Skip a layer and the whole engine underperforms - usually invisibly, until the metrics decay.
- Targeting & enrichment - qualified, signal-layered prospect lists. If the data isn't rich enough to write a personalized first line, the targeting isn't ready yet.
- Warming - building familiarity before the connection request. Profile views, post engagement, thoughtful comments. By the time the request arrives, the sender's name shouldn't be brand new to the prospect.
- Outreach & follow-up - the sequence itself, run with conditional logic so the next step depends on what the prospect did (accepted vs. viewed vs. replied vs. silent). See
{SKILL_BASE}/resources/sequences/dm-sequence.md. - Conversion - turning replies into booked meetings, with email as the support channel for prospects who engaged on LinkedIn but didn't convert there.
What ships with it
26 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- .claude/skills/copywriting/gt-SKILL.md 2.5 KB
- .claude/skills/infrastructure/gt-SKILL.md 2.2 KB
- .claude/skills/knowledge/gt-SKILL.md 2.4 KB
- .claude/skills/personas/gt-SKILL.md 1.9 KB
- .claude/skills/sequences/gt-SKILL.md 2.4 KB
- .claude/skills/strategy/gt-SKILL.md 2.2 KB
- .gitignore 181 B
- CHANGELOG.md 4.0 KB
- LICENSE 1.0 KB
- README.md 2.6 KB
- resources/copywriting/connection-notes.md 11 KB
- resources/copywriting/connection-request.md 9.0 KB
- resources/copywriting/copywriting.md 15 KB
- resources/copywriting/personalization.md 14 KB
- resources/infrastructure/rented-engine.md 25 KB
- resources/knowledge/heyreach-knowledge-base.md 15 KB
- resources/knowledge/lemlist-knowledge-base.md 7.5 KB
- resources/knowledge/linkedin-metrics-benchmarks.md 25 KB
- resources/personas/atl-messaging.md 11 KB
- resources/personas/btl-messaging.md 10 KB
- resources/sequences/dm-sequence.md 15 KB
- resources/sequences/drip-campaigns.md 15 KB
- resources/sequences/follow-up-system.md 16 KB
- resources/sequences/re-engagement.md 13 KB
- resources/strategy/campaign-strategy.md 15 KB
- resources/strategy/linkedin-first-engine.md 18 KB
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.
- 12d ago First seen · 218 lines · 235 tokens per session scan A 4562b2d224a5
gt-linkedin-outbound is a skill published in the GitHub repository Growth-Today/claude-skills (3 stars, last pushed today), licensed MIT. It adds 235 tokens to every session and 4,299 once invoked, about $0.0012 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 2026-08-31.
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