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 seaworld008/Commonly-used-high-value-skills --skill linkedingit clone --depth 1 https://github.com/seaworld008/Commonly-used-high-value-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/seaworld008/commonly-used-high-value-skills/linkedin)<a href="https://agentmods.dev/skills/seaworld008/commonly-used-high-value-skills/linkedin"><img src="https://agentmods.dev/badge/skills/seaworld008/commonly-used-high-value-skills/linkedin/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/seaworld008/commonly-used-high-value-skills/linkedin"><img src="https://agentmods.dev/badge/skills/seaworld008/commonly-used-high-value-skills/linkedin.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 | $0.00039 | $0.04779 |
| Opus 5.5 | $0.00016 | $0.01912 |
| Sonnet 5.5 | $0.00008 | $0.00956 |
| Haiku 4.5 | $0.00004 | $0.00478 |
Grade A, and why
linkedin 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 yesterday.
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.
This is a copy
89% identical to linkedin — 359 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 485 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Skill
You have access to linkedin – a CLI tool for LinkedIn automation. Use it to fetch profiles, search people and companies, send messages, manage connections, create posts, react, comment, and more.
Each command sends a request to Linked API, which runs a real cloud browser to perform the action on LinkedIn. Operations are not instant – expect 30 seconds to several minutes depending on complexity.
If linkedin is not available, install it:
npm install -g @linkedapi/linkedin-cli
Authentication
If a command fails with exit code 2 (authentication error), ask the user to set up their account:
- Go to app.linkedapi.io and sign up or log in
- Connect their LinkedIn account
- Copy the Linked API Token and Identification Token from the dashboard
The account owner completes authentication in their own secure local setup. Do not ask for tokens in chat or place them in command arguments. Inspect the installed CLI help for its supported secure configuration path; the following is a local setup responsibility, not an agent command:
Account owner: configure Linked API and Identification credentials locally.
Agent: retry only after the configured CLI reports authentication is available.
Global Flags
Always use --json and -q for machine-readable output:
LINKEDAPI_CLIENT=skill:linkedin linkedin <command> --json -q
When using this skill, run every linkedin ... example below with the
LINKEDAPI_CLIENT=skill:linkedin prefix so Linked API can attribute usage to the skill.
| Flag | Description |
|---|---|
--json |
Structured JSON output |
--quiet / -q |
Suppress stderr progress messages |
--fields name,url,... |
Select specific fields in output |
--no-color |
Disable colors |
--account "Name" |
Use a specific account for this command |
Output Format
Read the detailed procedure and examples when working on this part of the task.
What ships with it
2 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.
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.
- yesterday Changed · -11 lines 6f1c5f9d30ba
- 24d ago Changed 50c579731f4b
- 1mo ago Changed · -108 lines add2c7299b5d
- 1mo ago First seen · 604 lines · 39 tokens per session scan A c4730e0b4874
linkedin is a skill published in the GitHub repository seaworld008/Commonly-used-high-value-skills (73 stars, last pushed yesterday), licensed MIT. It adds 39 tokens to every session and 4,779 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 89% identical to linkedin, differing in 359 lines, and is treated as a copy.
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