X Agent Intelligence logo

X Agent Intelligence

Organization
dair-ai
x-agent-intelligence

Build or refresh a readable local AI and agent intelligence feed from the official X MCP server. Use when the user asks for an X-based digest, monitoring dashboard, daily AI feed, source-account timeline, or a self-contained HTML artifact backed by X posts.

Overview

Publisherdair-ai
Repositorydair-academy-plugins
Skill namex-agent-intelligence
Stars
614
Forks
64
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by dair-ai on GitHub. Read the source before you install it.

Installation

Install the X Agent Intelligence AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/dair-ai/dair-academy-plugins/tree/main/plugins/x-agent-intelligence/skills/x-agent-intelligence
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/dair-ai/dair-academy-plugins.git /tmp/dair-academy-plugins
mkdir -p .claude/skills
cp -r /tmp/dair-academy-plugins/plugins/x-agent-intelligence/skills/x-agent-intelligence .claude/skills/x-agent-intelligence
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable X Agent Intelligence in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads X Agent Intelligence on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so X Agent Intelligence is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

X Agent Intelligence

Create a local, readable HTML intelligence feed from X posts retrieved through the official X API MCP server. The feed is a presentation artifact, not a hosted application.

First check

Confirm that the agent can see an X MCP server. The expected official server is https://api.x.com/mcp. If no X tools are available, stop and point the user to references/x-mcp-setup.md; do not invent API responses or silently substitute scraping.

Read ../../references/x-mcp-setup.md when setup, authentication, client configuration, or portability matters.

Source configuration

Ask for or infer:

  • Source handles, without @.
  • Lookback window, normally 24 hours for a daily feed or 7 days for a backlog.
  • Categories such as Coding Agents, Frameworks, Agent Research, Papers, Models, and Meta.
  • Maximum stories per day, normally 10 to 25.
  • Output path and whether the user wants a static snapshot or a refreshable data-backed shell.

Keep source configuration separate from story content so users can edit it later.

If the user asks to begin with the shared public list, read ../../references/starter-sources.md. It is an optional starting point, not a requirement or a hidden default; users may edit or replace it.

Collect with X MCP

Use the official X MCP tools exposed by the user's client. Tool names may be namespaced by the client, but the expected operations are:

  1. Resolve handles with get_users_by_usernames, requesting id, name, username, profile_image_url, and verified.
  2. Fetch posts with get_users_posts for each resolved user. Use post.fields including created_at, text, author_id, public_metrics, entities, and attachments when supported. Use expansions for author_id, attachments.media_keys, and referenced_tweets.id when supported.
  3. If account feeds are unavailable, use search_posts_all with from:handle queries and explicit start_time/end_time windows.
  4. Fetch missing post details with get_posts_by_ids or get_posts_by_id.
  5. Use get_users_by_id only when an expanded author record is missing.

Do not use bookmark writes, Article publishing, likes, reposts, or other write tools for this skill. This workflow is read-only.

Normalize and select

Convert each post into this schema:

json
{
  "id": "post-id",
  "date": "YYYY-MM-DD",
  "created_at": "ISO timestamp",
  "category": "Models",
  "handle": "OpenAI",
  "author_name": "OpenAI",
  "verified": true,
  "profile_image_url": "https://...",
  "tweet_url": "https://x.com/OpenAI/status/post-id",
  "text": "raw text only when the user wants it retained",
  "title": "Short factual headline",
  "summary": "One or two sentences explaining why it matters.",
  "media_url": null,
  "media_type": null
}

Deduplicate by post ID. Exclude replies and reposts unless explicitly requested. Defensively remove any item with in_reply_to_user_id or a referenced_tweets entry of type replied_to or retweeted, even when the X MCP response ignored the requested exclusion. Prefer original announcements, papers, releases, benchmarks, demos, and concrete engineering reports. Rank using relevance, source quality, recency, engagement, and diversity across accounts. Do not let engagement alone determine importance.

Write titles and summaries as faithful paraphrases. Do not fabricate benchmarks, product capabilities, paper claims, or dates. Preserve the original post URL on every story.

Render the artifact

Build one self-contained feed.html, using ../../assets/reference-artifact.html as the design reference. Match its editorial reading-list layout closely: warm off-white canvas with a thin dark top rule; compact serif masthead; segmented story stats; a sticky, borderless category-chip toolbar; a narrow left date rail; and reading-list items with the title and "Why it matters" copy on the left and a fixed-size image or video preview on the right. Make the first story of the newest day the lead, with a larger thumbnail and headline.

Requirements:

  • Inline all normalized story data in the artifact. No backend, build step, scheduler controls, or external runtime dependencies; plain HTML, CSS, and JavaScript unless a framework is requested.
  • Include search, category filters, date grouping, source handles, avatars, original-post links, a clear updated timestamp, and image or video previews when media_url is available.
  • Include the source-settings control: it opens a panel where the user can add, remove, copy, and reset X handles. Persist handles only in browser local storage.
  • Use profile_image_url from X when available. Do not require unavatar.io.
  • Use X widget embeds only as an optional enhancement. The feed must remain readable if X widgets fail to load.
  • Seed the handle list from the adopter's own source configuration. The reference may seed the public handles from references/starter-sources.md, but never include credentials, private handles, automation identifiers, or orchestration configuration.
  • Do not expose MCP credentials in the artifact or browser JavaScript.

Validate before handing off

Check:

  • The output opens locally without a backend.
  • Every story has a valid X URL and handle.
  • Dates sort newest first.
  • Filters and search work with zero matching results.
  • Missing avatars, media, and embeds degrade gracefully.
  • No API key, bearer token, client secret, OAuth token, home-directory path, or private MCP URL appears in the output.
  • The artifact labels generated summaries as summaries and links to the original post.

If recurring updates are requested, explain that the user may run the same prompt from any scheduler or orchestrator they choose. X MCP remains the source-access layer.

Frequently asked questions

What does the X Agent Intelligence AI skill do?

Build or refresh a readable local AI and agent intelligence feed from the official X MCP server. Use when the user asks for an X-based digest, monitoring dashboard, daily AI feed, source-account timeline, or a self-contained HTML artifact backed by X posts.

Why use X Agent Intelligence on TypingMind?

Because you install it once and use it with any model. X Agent Intelligence is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install X Agent Intelligence in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/dair-ai/dair-academy-plugins/tree/main/plugins/x-agent-intelligence/skills/x-agent-intelligence. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use X Agent Intelligence?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with X Agent Intelligence?

As many as you like. As long as a model supports skills, you can use X Agent Intelligence with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the X Agent Intelligence AI skill free?

Yes. It is published on GitHub by dair-ai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇