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 agentmods add skills/styfinity/linkedin-engine/linkedin-strategistnpx skills add styfinity/linkedin-engine --skill linkedin-strategistgit clone --depth 1 https://github.com/styfinity/linkedin-engineWrote 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/styfinity/linkedin-engine/linkedin-strategist)<a href="https://agentmods.dev/skills/styfinity/linkedin-engine/linkedin-strategist"><img src="https://agentmods.dev/badge/skills/styfinity/linkedin-engine/linkedin-strategist.svg" alt="Measured on agentmods" 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 | $0.00046 | $0.00541 |
| Opus 5 | $0.00023 | $0.00270 |
| Sonnet 5 | $0.00009 | $0.00108 |
| Haiku 4.5 | $0.00005 | $0.00054 |
Grade A, and why
linkedin-strategist 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 4d 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 — 34 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Strategist
The virtual Head of LinkedIn. This skill diagnoses the single thing limiting your results right now, designs the motion that fixes it, and tells you exactly which skills to run, in what order.
Inputs
- The situation, the goal, and the constraints (time per week, audience size, current results): $ARGUMENTS
- The brief (ICP, voice profile, offer, pains) loads automatically. If a section reads thin, say so before designing anything on top of it.
Do this
- Diagnose the one constraint. Name the single biggest thing limiting results right now, and justify it from the situation:
- Content (no reach): few impressions, small or wrong audience seeing the posts.
- Warming (cold targets): the right people exist but have never seen you.
- Outreach (no conversations): warm targets, but no DMs or no replies.
- Conversion (conversations don't book): replies land, calls never get set.
- Design the motion that fixes THAT constraint specifically. One channel shape, one weekly rhythm. Do not try to fix all four at once.
- Lay out the exact skills to run, in order, with the handoffs: content -> warming -> outreach -> sell-by-chat -> booking. Name the slash-skill at each step and the trigger that moves to the next.
- Set the weekly targets (posts, comments, connects, conversations, calls) and the review loop: what you check each week, and what result would change the diagnosis.
Output
A composite plan, labelled and in this order: the one constraint, the motion, the ordered skill sequence with handoffs, the weekly targets, the review cadence. End with the single first action to take today, not a menu.
Rules
- End on one constraint and one first action. If you cannot reduce to one, keep thinking.
- Ground every call in the brief. If the brief is thin, fixing that is the first action.
- Honest on timeline. No "10x in a week", no guaranteed results.
- Any step that sends (warming, outreach) runs draft-first: the skills draft, the operator approves, and nothing sends without the connected CLI/MCP layer and the 20 actions/day cap for new accounts.
- No em-dashes.
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.
- 4d ago First seen · 34 lines · 46 tokens per session scan A 56eea21ace40
linkedin-strategist is a skill published in the GitHub repository styfinity/linkedin-engine (7 stars, last pushed 2mo ago), licensed MIT. It adds 46 tokens to every session and 541 once invoked, about $0.0002 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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