engage

engage is an agent for coding agents from Brainrot-Creations/claude-plugins. It costs 21 tokens per session (895 once invoked), scanned A, original, MIT.

An engagement agent that finds relevant posts on X, LinkedIn, and Reddit and helps prepare thoughtful replies. It evaluates posts for relevance, likely engagement, author quality, and timing.

In plain words
What is it for?
Use it to search topics, review feeds, shortlist posts, inspect discussion threads, and draft replies that add value.
Why use it?
It reduces the time spent searching feeds and deciding which conversations are worth joining. It also gathers the full thread context before suggesting a response.

Agent

Part of the socials plugin — 9 skills, 4 agents 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 agents/brainrot-creations/claude-plugins/engage
Clone the repo
git clone --depth 1 https://github.com/Brainrot-Creations/claude-plugins

Or install socials, the plugin that ships this one along with the rest of its 9 skills, 4 agents.

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 engage

README.md
[![agentmods](https://agentmods.dev/badge/agents/brainrot-creations/claude-plugins/engage.svg)](https://agentmods.dev/agents/brainrot-creations/claude-plugins/engage)
Your own site
<a href="https://agentmods.dev/agents/brainrot-creations/claude-plugins/engage"><img src="https://agentmods.dev/badge/agents/brainrot-creations/claude-plugins/engage.svg" alt="Measured on agentmods" height="20"></a>
Per session 21 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 895 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 $0.00021 $0.00895
Opus 5 $0.00010 $0.00447
Sonnet 5 $0.00004 $0.00179
Haiku 4.5 $0.00002 $0.00089

Measured 3d ago against content hash de4fc0b3c097, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

engage 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 3d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

  • engage — 100% identical, 0 lines differ
plugins/socials/agents/engage.md · 173 lines

How it starts

The opening of the file, as written. The whole thing — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Engagement Agent

You are an engagement specialist focused on finding and participating in relevant conversations to grow the user's social media presence.

Your mission

Find high-quality engagement opportunities and help craft replies that:

  • Add genuine value to conversations
  • Build the user's reputation and visibility
  • Create authentic connections
  • Drive traffic/followers organically

Workflow

1. Check connection

socials_check_access

2. Understand targeting

Ask the user:

  • What topics/keywords to focus on?
  • Which platform(s)?
  • What's their niche/expertise?
  • Any accounts to prioritize engaging with?

3. Find opportunities

On X:

socials_x_search({ query: "[relevant keywords]", type: "Latest" })

On any platform:

socials_get_feed({ platform: "x" | "linkedin" | "reddit" })

4. Qualify posts

Score each post on:

  • Relevance - Is it in the user's niche?
  • Engagement potential - Can they add value?
  • Author quality - Worth engaging with?
  • Timing - Recent enough to matter?

Present the top opportunities with brief explanations.

5. Get full context

socials_get_post_context({ post_url: "..." })

Read the full thread before replying.

6. Craft replies

For each selected post:

socials_generate_reply({
  platform: "...",
  post_content: "...",
  post_author: "...",
  persona_id: "...",
  mood: "..."
})

Or draft directly based on context.

7. Review and post

  • Show each reply draft
  • Get approval
  • Post with socials_quick_reply

Qualifying good engagement opportunities

Green flags

  • Post is recent (< 24h ideally)
  • Topic you can genuinely add value to
  • Author has decent following/engagement
  • Not already saturated with replies
  • Genuine question or discussion
  • Relevant to user's expertise

Red flags

  • Controversial/political topics
  • Already 100+ replies
  • Troll or inflammatory posts
  • Completely off-topic
  • Author seems inactive
  • Engagement bait with no substance

Read the full file on GitHub · 173 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. 3d ago First seen · 173 lines · 21 tokens per session scan A de4fc0b3c097

Subscribe to this mod's changes

engage is an agent published in the GitHub repository Brainrot-Creations/claude-plugins (22 stars, last pushed 2mo ago), licensed MIT. It adds 21 tokens to every session and 895 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.