post

post is a command for coding agents from rockyco/claude-linkedin-plugin. It costs 25 tokens per session (2,098 once invoked), scanned A, original, MIT.

A command that prepares a LinkedIn post as local text and image files for you to review and upload yourself. LinkedIn is a professional social network.

In plain words
What is it for?
Creating text posts, single-image announcements, or PDF carousels for technical, business, or explanatory content.
Why use it?
It keeps drafting and file preparation in the project while leaving the final review and publishing step under your control.

Command

Part of the linkedin plugin — 1 skill, 4 commands shipped together

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 commands/rockyco/claude-linkedin-plugin/post
Clone the repo
git clone --depth 1 https://github.com/rockyco/claude-linkedin-plugin

Or install linkedin, the plugin that ships this one along with the rest of its 1 skill, 4 commands.

Wrote 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.

agentmods badge for post

README.md
[![agentmods](https://agentmods.dev/badge/commands/rockyco/claude-linkedin-plugin/post.svg)](https://agentmods.dev/commands/rockyco/claude-linkedin-plugin/post)
Your own site
<a href="https://agentmods.dev/commands/rockyco/claude-linkedin-plugin/post"><img src="https://agentmods.dev/badge/commands/rockyco/claude-linkedin-plugin/post.svg" alt="Measured on agentmods" height="20"></a>
Per session 25 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,098 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. 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 $0.00025 $0.02098
Opus 5 $0.00013 $0.01049
Sonnet 5 $0.00005 $0.00420
Haiku 4.5 $0.00003 $0.00210

Measured 4d ago against content hash dbf20215a91b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

post 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.

commands/post.md · 182 lines

How it starts

The opening of the file, as written. The whole thing — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.

LinkedIn Post (Local Bundle)

Produce a LinkedIn-ready bundle locally. The user reviews the files and uploads manually via https://www.linkedin.com/feed/?shareActive=true. This command does not call the LinkedIn API.

Follow the linkedin-api skill for 2026-algorithm-optimized content rules (dwell-time hook, 1000-1300 char body, numbered carousel frameworks, no engagement bait, 3-5 hashtags, no em-dashes, no external URLs).

Step 1 - Pick the target directory

Default: <project-root>/docs/linkedin/. Fall back to <project-root>/linkedin/ if docs/ does not exist.

If the working directory does not look like a project root or the location is ambiguous, use AskUserQuestion to confirm.

Create the directory if missing:

mkdir -p "<project>/docs/linkedin"

Step 2 - Decide the format

Default by content type:

  • Technical / B2B / explanatory -> PDF document carousel (5-10 slides at 1080x1080). Highest 2026 engagement.
  • Opinion, discussion, short take -> text-only
  • Announcement / launch with one visual -> single image (1200x627)

If unclear, ask:

What format? options:
  1) PDF carousel (5-10 slides, highest engagement, recommended for technical content)
  2) Multi-image carousel (2-9 PNGs, similar engagement, quicker to produce)
  3) Single image (1200x627, lowest engagement but simple)
  4) Text only (short discussion-style post)

Step 3 - Draft and save the post text

Apply every rule from the linkedin-api skill. Summary:

  • First 3 lines hook the reader (contrarian, unexpected stat, high-stakes problem, origin, or question)
  • Body 1000-1300 chars, 2-3 line paragraphs with white space
  • No em-dashes, no "Comment YES" / "DM me" / "link in comment" bait, no polls
  • Close with an open question CTA (5+ word reply invited)
  • 3-5 hashtags on the last line(s), first tag is the most relevant

Write to <dir>/post.txt:

# Use the Write tool (not bash heredoc) for multi-line text.

Validate:

wc -c <dir>/post.txt                  # aim for 1000-1300, hard cap 3000
grep -cE '—|–' <dir>/post.txt         # em-dash count should be 0
grep -ciE 'comment yes|dm me|follow for more|tag someone|like this post to' <dir>/post.txt  # banned bait
grep -cE '^#' <dir>/post.txt          # sanity

Read the full file on GitHub · 182 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. 4d ago First seen · 182 lines · 25 tokens per session scan A dbf20215a91b

Subscribe to this mod's changes

post is a command published in the GitHub repository rockyco/claude-linkedin-plugin (2 stars, last pushed 1mo ago), licensed MIT. It adds 25 tokens to every session and 2,098 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 2026-08-31.

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