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-followup-adapternpx skills add styfinity/linkedin-engine --skill linkedin-followup-adaptergit 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-followup-adapter)<a href="https://agentmods.dev/skills/styfinity/linkedin-engine/linkedin-followup-adapter"><img src="https://agentmods.dev/badge/skills/styfinity/linkedin-engine/linkedin-followup-adapter.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 | $0.00047 | $0.00527 |
| Opus 5 | $0.00023 | $0.00264 |
| Sonnet 5 | $0.00009 | $0.00105 |
| Haiku 4.5 | $0.00005 | $0.00053 |
Grade A, and why
linkedin-followup-adapter 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.
What it actually says
LinkedIn Follow-up Adapter
A follow-up is a new move, not a reminder. This skill reads the real state of the conversation and writes the next message off THAT, adding a fresh piece of value every time.
Inputs
- The thread so far and what actually happened on the last touch (they replied and went quiet, they opened a loop, they raised an objection, they ghosted after a yes): $ARGUMENTS
- The brief (persona tone, pains, offer) loads automatically.
Do this
- Read where the conversation actually is. Name the real state in one line: warm-but-busy, half-objection, interest-without-action, or genuine silence. Write off that, not a calendar.
- Pick a new angle, different from the last touch. If the last message asked a question, this one gives. If the last gave value, this one references a signal or a result.
- Add one new piece of value: a relevant observation, a useful resource, a specific result a client or operator saw, a single sharp question. Never restate the prior ask.
- Write the message short and human. Reads like a peer continuing a real thread.
- If their reply signals heat, hand it to /linkedin-reply-triager instead of sending another nudge. Run /linkedin-humanizer on the draft before it ships.
Output
- The next message, labelled clearly.
- The angle it takes and the conversation state it answers, one line.
- When to send it, expressed relative to the last touch, not a fixed date.
Rules
- State-driven, never timer-driven. The thread tells you when and what, not the clock.
- New angle and new value on every touch. If you cannot add value, do not send.
- Banned phrase: "just following up" (and its cousins "bumping this", "circling back", "checking in").
- No em-dashes. No "hope you're well".
- Draft only. Claude drafts, the operator approves. Sending runs through the connected CLI/MCP layer on the operator's own session or provider key, shows the draft first, and is capped at 20 actions per day for new accounts.
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 · 33 lines · 47 tokens per session scan A 5017ef857a11
linkedin-followup-adapter is a skill published in the GitHub repository styfinity/linkedin-engine (7 stars, last pushed 2mo ago), licensed MIT. It adds 47 tokens to every session and 527 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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