Borrowing it
Nothing to install: this file belongs to Othmane-Khadri/YALC-the-GTM-operating-system. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Othmane-Khadri/YALC-the-GTM-operating-system/main/.claude/skills/launch-linkedin-campaign/SKILL.mdgit clone --depth 1 https://github.com/Othmane-Khadri/YALC-the-GTM-operating-systemWrote 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/othmane-khadri/yalc-the-gtm-operating-system/launch-linkedin-campaign)<a href="https://agentmods.dev/skills/othmane-khadri/yalc-the-gtm-operating-system/launch-linkedin-campaign"><img src="https://agentmods.dev/badge/skills/othmane-khadri/yalc-the-gtm-operating-system/launch-linkedin-campaign/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/othmane-khadri/yalc-the-gtm-operating-system/launch-linkedin-campaign"><img src="https://agentmods.dev/badge/skills/othmane-khadri/yalc-the-gtm-operating-system/launch-linkedin-campaign.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 5 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 106 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 125 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium Rogue Agent · line 34 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
- medium MCP Rug Pull · line 107 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 126 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00134 | $0.02137 |
| Opus 5 | $0.00067 | $0.01069 |
| Sonnet 5 | $0.00027 | $0.00427 |
| Haiku 4.5 | $0.00013 | $0.00214 |
Grade A, and why
launch-linkedin-campaign 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 — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Launch LinkedIn Campaign
I'll wrap two CLI commands — campaign:create (creates the campaign + pulls qualified leads from the holding pool) and campaign:create-sequence (drafts the connect→DM1→DM2 sequence). Both side-effecting → both shell-out per the 0.13.0 architecture.
When This Skill Applies
Use this skill when the user says:
- "launch a LinkedIn campaign for these leads"
- "send a LinkedIn outreach to this list"
- "start the outbound to the qualified leads"
- "run the LinkedIn sequence on this result set"
- "fire the connect-then-DM flow"
NOT this skill (use qualify-leads instead):
- "score these leads first" / "qualify the engagers" — qualification runs the 7-gate pipeline. Run that BEFORE this skill.
NOT this skill (use personalize-message instead):
- "personalize a single DM" — that's per-lead copy. This skill handles bulk sequence generation.
NOT this skill (use scrape-post-engagers instead):
- "pull who liked this post" — that produces a result set. This skill consumes a holding pool of qualified leads.
What This Skill Does
- Hypothesis gate. Before doing anything, checks that the outbound hypothesis is recorded —
~/.gtm-os/frameworks/installed/outreach-campaign-builder.hypothesis.jsonmust exist. If missing: refuses to launch and routes the user toframework:set-hypothesis(or setup Step 10). - Asks for campaign title + optional leads filter + sequence YAML + source CSV/JSON path.
- Shells out to
campaign:createto write the campaign row + pull qualified leads from the holding pool. - Shells out to
campaign:create-sequenceto draft the connect→DM1→DM2 sequence. - Renders both results + asks "ready to send?" — does not auto-trigger sending.
- Suggests enabling
campaign:trackcron (or running it manually) for monitoring.
Pre-flight (before Step 1)
Onboarding interruption guard
test -f ~/.gtm-os/.in-flight-setup && echo "BLOCKED" || echo "OK"
If BLOCKED, stop. Tell the user to finish yalc-gtm start first.
What ships with it
1 file 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.
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 · 164 lines · 134 tokens per session scan A 45ff9643a72e
launch-linkedin-campaign is a skill published in the GitHub repository Othmane-Khadri/YALC-the-GTM-operating-system (301 stars, last pushed 22d ago), licensed MIT. It adds 134 tokens to every session and 2,137 once invoked, about $0.0007 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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kn-research
Use when you need to understand existing code, find patterns, search project knowledge, investigate current external facts, or explore a large codebase before implementation.
kn-debug
Use when debugging errors, test failures, build issues, or blocked tasks — structured triage to fix to learn.