linkedincli AGENTS.md

Reference instructions for an AI agent that uses a command-line tool to manage LinkedIn profiles and posts. They explain authentication, available commands, and safe local handling of LinkedIn session data.

In plain words
What is it for?
They help an agent log in, inspect profiles, and create, edit, or delete LinkedIn posts through the CLI or its MCP server.
Why use it?
They reduce guesswork about which LinkedIn actions are available and how to authenticate. They also clarify that live session data and LinkedIn requests must stay on the operator’s own computer.

Instructions file for CodexOpenCode

Install

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.

agentmods
npx agentmods add instructions/bcharleson/linkedincli/agents-md
Clone the repo
git clone --depth 1 https://github.com/bcharleson/linkedincli

Made for: Codex, OpenCode.

Per session 5,053 This file is loaded in full into every session.
When invoked 5,053 The same file — it is already loaded in full.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.05053 $0.05053
Opus 5 $0.02527 $0.02527
Sonnet 5 $0.01011 $0.01011
Haiku 4.5 $0.00505 $0.00505

Measured 2d ago against content hash b87628281ecc, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

linkedincli AGENTS.md scanned grade A with 1 finding 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 2d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

LINKEDIN_HTTP=curl-impersonate # local curl_chrome123 (opt-in)
AGENTS.md · 663 lines

How it starts

The opening of the file, as written. The whole thing — 663 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — LinkedIn CLI Tool Reference for AI Agents

This file documents every tool available in the LinkedIn CLI / MCP server. AI agents (Claude Code, Cursor, Windsurf, OpenClaw, etc.) should use this as the authoritative reference for managing LinkedIn.

Authentication

Local harness only. A live LinkedIn session (cookies, Chrome cookie import, Voyager API calls) must run on the operator's own computer (laptop or Mac mini). Cloud agents and Grok Bot must not set session cookies or call Voyager. Safe remote use is: install the linkedin CLI binary, or call an MCP server already running on the local harness. Cookies and Voyager calls never leave that machine.

On the local harness, session cookies are stored in ~/.linkedin-cli/config.json after linkedin login, or set via environment variables:

LINKEDIN_LI_AT=<your li_at cookie>
LINKEDIN_JSESSIONID=<your JSESSIONID cookie>

Optional local-only session-survival settings (see README). Default Node fetch is often TLS-fingerprinted and LinkedIn may invalidate li_at immediately:

LINKEDIN_HTTP=curl-impersonate          # local curl_chrome123 (opt-in)
LINKEDIN_CURL_IMPERSONATE_BIN=...       # override binary path on this machine
LINKEDIN_FROM_CHROME=1                  # read cookies from a local Chrome profile
LINKEDIN_CHROME_PROFILE=Default         # Chrome profile directory name

CLI equivalents: --from-chrome, --chrome-profile <name>. These read the local Chrome profile and must not be used from a remote runner.

To check if the session is valid (local harness):

linkedin status --verify

Tool Reference

Profile Tools

profile_me

Get the authenticated user's own LinkedIn profile.

linkedin profile me

Parameters: None Returns: Full profile object (firstName, lastName, headline, entityUrn, publicIdentifier, etc.)


profile_view

View any LinkedIn profile by their public identifier (the URL slug).

linkedin profile view johndoe

Parameters:

Name Type Required Description
public_id string yes The public profile identifier from their LinkedIn URL

Read the full file on GitHub · 663 lines

Changes

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.

  1. 2d ago First seen · 663 lines · 5,053 tokens per session scan A b87628281ecc

Subscribe to this mod's changes

linkedincli AGENTS.md is an instructions file published in the GitHub repository bcharleson/linkedincli (56 stars, last pushed 10d ago), licensed MIT. It adds 5,053 tokens to every session, about $0.0253 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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