X (Twitter) Scraper — Xquik

Overview

This public intake copy packages

plugins/antigravity-awesome-skills-claude/skills/x-twitter-scraper

https://github.com/sickn33/antigravity-awesome-skills

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses

metadata.json

ORIGIN.md

X (Twitter) Scraper — Xquik

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Capabilities, Repository, Limitations.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• User needs to search X/Twitter for tweets by keyword, hashtag, or user
• User wants to look up a user profile (bio, follower counts, etc.)
• User needs engagement metrics for a specific tweet (likes, retweets, views)
• User wants to check if one account follows another
• User needs to extract followers, replies, retweets, quotes, or community members in bulk
• User wants to run a giveaway draw from tweet replies

Operating Table

metadata.json

ORIGIN.md

SKILL.md

SKILL.md

## Related Skills

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Sign up at xquik.com
2. Generate an API key from the dashboard
3. Set it as an environment variable or pass it directly
4. Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
5. Read the overview and provenance files before loading any copied upstream support files.
6. Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.
7. Execute the upstream workflow while keeping provenance and source boundaries explicit in the working notes.

Imported Workflow Notes

Imported: Setup

Install the Skill

npx skills add Xquik-dev/x-twitter-scraper

Or clone manually into your agent's skills directory:

# Claude Code
git clone https://github.com/Xquik-dev/x-twitter-scraper.git .claude/skills/x-twitter-scraper

# Cursor / Codex / Gemini CLI / Copilot
git clone https://github.com/Xquik-dev/x-twitter-scraper.git .agents/skills/x-twitter-scraper

Get an API Key

1. Sign up at xquik.com
2. Generate an API key from the dashboard
3. Set it as an environment variable or pass it directly

export XQUIK_API_KEY="xq_YOUR_KEY_HERE"

Imported: Overview

Gives your AI agent full access to X (Twitter) data through the Xquik platform. Covers tweet search, user profiles, follower extraction, engagement metrics, giveaway draws, account monitoring, webhooks, and 19 bulk extraction tools — all via REST API or MCP server.

Imported: Capabilities

Examples

Example 1: Ask for the upstream workflow directly

Use @x-twitter-scraper to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @x-twitter-scraper against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @x-twitter-scraper for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @x-twitter-scraper using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Imported Usage Notes

Imported: Examples

Search tweets:

"Search X for tweets about 'claude code' from the last week"

Look up a user:

"Who is @elonmusk? Show me their profile and follower count"

Check engagement:

"How many likes and retweets does this tweet have? https://x.com/..."

Run a giveaway:

"Pick 3 random winners from the replies to this tweet"

Monitor an account:

"Monitor @openai for new tweets and notify me via webhook"

Bulk extraction:

"Extract all followers of @anthropic"

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
• Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.
• Keep provenance, source commit, and imported file paths visible in notes and PR descriptions.
• Point directly at the copied upstream files that justify the workflow instead of relying on generic review boilerplate.
• Treat generated examples as scaffolding; adapt them to the concrete task before execution.
• Route to a stronger native skill when architecture, debugging, design, or security concerns become dominant.

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in

plugins/antigravity-awesome-skills-claude/skills/x-twitter-scraper

metadata.json

ORIGIN.md

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated

SKILL.md

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @00-andruia-consultant-v2

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @10-andruia-skill-smith-v2

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @20-andruia-niche-intelligence-v2

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @3d-web-experience-v2

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

references

references/n/a

examples

examples/n/a

scripts

scripts/n/a

agents

agents/n/a

assets

assets/n/a

Imported Reference Notes

Imported: API Reference

/x/tweets/{id}

/x/tweets/search

/x/users/{username}

/x/followers/check

/trends

/monitors

/events

/webhooks

/draws

/extractions

/extractions/estimate

/account

Base URL:

https://xquik.com/api/v1

x-api-key: xq_...

https://xquik.com/mcp

Imported: Repository

https://github.com/Xquik-dev/x-twitter-scraper

Maintained By: Xquik

Imported: Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.