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/abdulrbasit/job-hunter/linkedinnpx skills add abdulrbasit/job-hunter --skill linkedingit clone --depth 1 https://github.com/abdulrbasit/job-hunterWrote 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/abdulrbasit/job-hunter/linkedin)<a href="https://agentmods.dev/skills/abdulrbasit/job-hunter/linkedin"><img src="https://agentmods.dev/badge/skills/abdulrbasit/job-hunter/linkedin.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 5.1 | $0.00023 | $0.00417 |
| Opus 5 | $0.00012 | $0.00209 |
| Sonnet 5 | $0.00005 | $0.00083 |
| Haiku 4.5 | $0.00002 | $0.00042 |
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 6d 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 Command Center
Arguments: $ARGUMENTS
Safety Rules
- Never post, send, connect, follow, like, or comment automatically.
- All output is draft only — user reviews before any action.
- No fabricated proof points, contacts, or outcomes.
Routing
Normalize the first argument to lowercase. Empty argument → show menu.
ideas,post,content: execute.claude/skills/linkedin/modes/ideas.mdinline.draft,write: execute.claude/skills/linkedin/modes/draft.mdinline with remaining arguments.engage,comments: execute.claude/skills/linkedin/modes/engage.mdinline with remaining arguments.network,connect: execute.claude/skills/linkedin/modes/network.mdinline.
Unknown mode → print the command menu and ask the user to choose a listed mode.
Command Menu
LinkedIn Command Center
/linkedin ideas Generate weekly post ideas grounded in your job-search evidence
/linkedin draft <ref> Write one ready-to-post draft from an approved idea
/linkedin engage Draft comments for posts you paste in
/linkedin network Build a weekly connection queue from active job targets
Output Rules
- Execute child modes inline from their mode file; do not print a slash command as a handoff.
- Leave all generated content uncommitted. Run /job-hunter finalize after review.
What ships with it
4 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.
- 6d ago First seen · 48 lines · 23 tokens per session scan A f3df4793f95a
linkedin is a skill published in the GitHub repository abdulrbasit/job-hunter (24 stars, last pushed 1mo ago), licensed MIT. It adds 23 tokens to every session and 417 once invoked, about $0.0001 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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