engage

engage is a skill for Claude Code, Codex from Epistates/sparX. It costs 50 tokens per session (2,612 once invoked), scanned A, original, MIT.

A browser-based tool for reviewing replies and conversations on X, drafting responses, and posting them after the user approves.

In plain words
What is it for?
Reviewing replies to a post, checking mentions and notifications, selecting comments worth answering, drafting replies, and posting approved responses.
Why use it?
It helps find useful comments and manage follow-up conversations without manually searching through every reply.

Skill for Claude CodeCodex

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 skills/epistates/sparx/engage
Any agent
npx skills add Epistates/sparX --skill engage
Clone the repo
git clone --depth 1 https://github.com/Epistates/sparX

Made for: Claude Code, Codex.

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/skills/epistates/sparx/engage.svg)](https://agentmods.dev/skills/epistates/sparx/engage)
Your own site
<a href="https://agentmods.dev/skills/epistates/sparx/engage"><img src="https://agentmods.dev/badge/skills/epistates/sparx/engage.svg" alt="Measured on agentmods" height="20"></a>
Per session 50 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,612 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 $0.00050 $0.02612
Opus 5 $0.00025 $0.01306
Sonnet 5 $0.00010 $0.00522
Haiku 4.5 $0.00005 $0.00261

Measured 4d ago against content hash 2c15df688513, 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 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.

.claude/skills/engage/SKILL.md · 258 lines

How it starts

The opening of the file, as written. The whole thing — 258 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Engage — Conversation Velocity via Browser

Manage replies on your X posts to activate the 75–150× author reply conversation multiplier. This skill surfaces comments worth replying to, drafts high-quality replies, and posts them with your approval.

Why this matters: Author replies to comments create conversation threads — the single highest-weight signal in the Phoenix algorithm at 75–150× a like. A post with 5 author reply threads massively outperforms one with none.

Input

The user provides one of:

  • A post URL — engage with replies on that specific post
  • "notifications" — review recent mentions and replies across all posts
  • "replies" — same as notifications, focused on reply tab
  • Nothing — defaults to notifications

Process

Step 1 — Get Browser Context

mcp__claude-in-chrome__tabs_context_mcp(createIfEmpty: true)

Step 2 — Navigate

For a specific post:

mcp__claude-in-chrome__navigate(url: "<post_url>", tabId: <tab>)
mcp__claude-in-chrome__computer(action: "wait", duration: 3, tabId: <tab>)

For notifications:

mcp__claude-in-chrome__navigate(url: "https://x.com/notifications", tabId: <tab>)
mcp__claude-in-chrome__computer(action: "wait", duration: 3, tabId: <tab>)

Take a screenshot to verify state:

mcp__claude-in-chrome__computer(action: "screenshot", tabId: <tab>)

If not logged in, stop and tell the user to log in manually.

Step 3 — Collect Comments / Mentions

On a specific post:

  1. Scroll through the replies section below the post:
mcp__claude-in-chrome__get_page_text(tabId: <tab>)
  1. Use JavaScript to extract reply content:
mcp__claude-in-chrome__javascript_tool(action: "javascript_exec", text: "
  const articles = document.querySelectorAll('article');
  const replies = Array.from(articles).slice(1).map((article, i) => {
    const text = article.innerText;
    const ariaLabels = Array.from(article.querySelectorAll('[aria-label]'))
      .map(el => el.getAttribute('aria-label'));
    return { index: i, text: text.substring(0, 300), meta: ariaLabels.slice(0, 5) };
  });
  JSON.stringify(replies.slice(0, 15), null, 2);
", tabId: <tab>)

Read the full file on GitHub · 258 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 · 258 lines · 50 tokens per session scan A 2c15df688513

Subscribe to this mod's changes

engage is a skill published in the GitHub repository Epistates/sparX (3 stars, last pushed 5mo ago), licensed MIT. It adds 50 tokens to every session and 2,612 once invoked, about $0.0003 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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