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/scrape-post-engagers/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/scrape-post-engagers)<a href="https://agentmods.dev/skills/othmane-khadri/yalc-the-gtm-operating-system/scrape-post-engagers"><img src="https://agentmods.dev/badge/skills/othmane-khadri/yalc-the-gtm-operating-system/scrape-post-engagers/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/scrape-post-engagers"><img src="https://agentmods.dev/badge/skills/othmane-khadri/yalc-the-gtm-operating-system/scrape-post-engagers.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
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 →
- medium MCP Rug Pull · line 33 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 68 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 | $0.00114 | $0.01373 |
| Opus 5 | $0.00057 | $0.00687 |
| Sonnet 5 | $0.00023 | $0.00275 |
| Haiku 4.5 | $0.00011 | $0.00137 |
Grade A, and why
scrape-post-engagers 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 — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scrape Post Engagers
I'll pull the people who engaged with a LinkedIn post (reactors + commenters) via Unipile, dedupe them across endpoints, and persist the result as a numbered result set you can hand off to qualify-leads or launch-linkedin-campaign.
When This Skill Applies
Use this skill when the user says:
- "scrape engagers from this post"
- "who liked this LinkedIn post"
- "who commented on this LinkedIn post"
- "pull engagers from this URL"
- "get the audience of this post"
NOT this skill (use qualify-leads instead):
- "score these prospects" / "qualify these leads" — qualification runs the 7-gate ICP pipeline on an existing result set, it doesn't fetch new data.
NOT this skill (use personalize-message instead):
- "write a DM to this engager" / "personalize a message" — that's per-lead copy generation, not audience extraction.
NOT this skill (use launch-linkedin-campaign instead):
- "send connect requests to these people" / "start outreach" — campaign launch consumes a result set; it doesn't produce one.
What This Skill Does
- Validates the LinkedIn post URL (
linkedin.com/posts/...orlinkedin.com/feed/update/...). - Shells out to
npx tsx src/cli/index.ts leads:scrape-post --url <url>. - The CLI calls Unipile under the hood, fetches reactors + commenters, dedupes them, writes them to the local SQLite DB as a fresh result set, and prints the result set id, totals, and output path.
- Renders a clean summary and offers to chain into the next step (qualify or launch).
What This Skill Does NOT
- Send messages, connection requests, or DMs. That's
launch-linkedin-campaign. - Score or filter the engagers against an ICP. That's
qualify-leads --result-set <id>. - Personalize copy. That's
personalize-message. - Edit
.env, the Unipile DSN, or any config. Read the env, fail loudly if missing.
Workflow
Step 0: Ask for the LinkedIn post URL
If the user hasn't pasted a post URL, ask:
"What's the LinkedIn post URL? I need either the activity URL (
linkedin.com/posts/<handle>_<slug>-activity-...) or the feed update URL (linkedin.com/feed/update/urn:li:activity:...)."
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 · 120 lines · 114 tokens per session scan A 534f3790ddce
scrape-post-engagers 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 114 tokens to every session and 1,373 once invoked, about $0.0006 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-flow
Use when orchestrating a full Knowns spec or task wave through planning, implementation, review, integration, and verification, optionally using sub-agents when scopes are parallel-safe.
kn-debug
Use when debugging errors, test failures, build issues, or blocked tasks — structured triage to fix to learn.
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.