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 Kubis010/linkedin-mcp-server-salesbot --skill salesbot-outreachgit clone --depth 1 https://github.com/Kubis010/linkedin-mcp-server-salesbotWrote 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/kubis010/linkedin-mcp-server-salesbot/salesbot-outreach)<a href="https://agentmods.dev/skills/kubis010/linkedin-mcp-server-salesbot/salesbot-outreach"><img src="https://agentmods.dev/badge/skills/kubis010/linkedin-mcp-server-salesbot/salesbot-outreach/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/kubis010/linkedin-mcp-server-salesbot/salesbot-outreach"><img src="https://agentmods.dev/badge/skills/kubis010/linkedin-mcp-server-salesbot/salesbot-outreach.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 | $0.00054 | $0.00642 |
| Opus 5.5 | $0.00022 | $0.00257 |
| Sonnet 5.5 | $0.00011 | $0.00128 |
| Haiku 4.5 | $0.00005 | $0.00064 |
Grade A, and why
salesbot-outreach 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 — 37 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Targeted LinkedIn outreach with Salesbot
Salesbot is built for a few well-chosen people, not bulk blasting. Prefer 5 strong leads over 50 weak ones.
Before anything else
get_linkedin_status— if the account is not connected, callconnect_linkedinand give the user the link. Stop until it is connected.get_daily_limits— know how many invitations and messages are left today. Never try to work around a limit.
Finding people
-
Known role and place:
search_linkedin_people(results are not saved). -
A Sales Navigator search or list URL from the user:
search_linkedin_navigator. -
Companies first:
import_linkedin_company_list→list_companies→ research withsearch_web→update_company_research→ find the decision-maker withsearch_linkedin_people. -
Companies that are hiring:
search_job_postings→get_job_posting_details(itshiring_teamis the person to contact). -
About a company:
read_company_websitewith its homepage (max 60 a day) gives a short profile and generic e-mails; save the summary with its source URLs viaupdate_company_research. Never put a found e-mail into outreach without the user's decision.
Save every person you want to keep with upsert_linkedin_contact (pass prospect_company_id when you have it). Check check_blacklist before contacting a company.
Research
enrich_contacts (max 8 per call) loads the full profile. It visits the profile on LinkedIn, so enrich only people you really intend to contact. Use get_lead_context for everything Salesbot already knows about a lead.
Contacting
- For more than one or two people, use a campaign (see the
salesbot-campaignskill): it paces the sending and keeps the account safe. - One-off actions:
send_connection_request,send_linkedin_message,reply_to_chat. Write the message for that person — mention something concrete from their profile or company. - If a tool answers
APPROVAL_REQUIRED, the message waits for the user in the Salesbot app. Tell the user; never say it was sent.
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 · 37 lines · 54 tokens per session scan A 650cd3411a03
salesbot-outreach is a skill published in the GitHub repository Kubis010/linkedin-mcp-server-salesbot (1 stars, last pushed 8d ago), licensed MIT. It adds 54 tokens to every session and 642 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-04.
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