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Agent skill

Bggg Data X

by binggandata in binggandata/bggg-skills

Collect auditable public X/Twitter posts by controlling the user's already logged-in Chrome, searching X's rendered web interface, scrolling visible results, and extracting original post text and…

MITAuto-check passedBackend & APIs

Install Bggg Data X

skills CLI
$ npx skills add binggandata/bggg-skills --skill bggg-data-x -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install binggandata/bggg-skills bggg-data-x --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/binggandata/bggg-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/bggg-data-x .claude/skills/bggg-data-x && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
bggg-data-x
GitHub stars
605
Token cost
~1.5k tokens
SKILL.md length
573 words
Files
6 (incl. scripts, references)
Skills in repo
13
Repo updated
First seen
Licence
MIT

At a glance

Collect auditable public X/Twitter posts by controlling the user's already logged-in Chrome, searching X's rendered web interface, scrolling visible results, and extracting original post text and…

  • Works in 4 steps: Use the Chrome plugin and follow its… → Open the first planned search URL.… → For each query, collect only rendered… → …
  • Social listening
  • SKILL.md covers VOC Project Layout（bggg 系列共用）, Workflow, Required DOM Contract and Quality and Safety Rules, plus 3 more sections
  • Runs Python scripts from its folder; calls python3

What it does

Bggg Data X is an agent skill from binggandata/bggg-skills. Collect auditable public X/Twitter posts by controlling the user's already logged-in Chrome, searching X's rendered web interface, scrolling visible results, and extracting original post text and metadata from DOM into normalized JSONL. Use for VOC research, social listening, multilingual keyword discovery, competitor monitoring, or historical search when X requires the user's browser session and cookies, credentials, internal GraphQL, paid APIs, or search-engine snippets must not be exported or used. X data…

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including scripts and reference files (for example `agents/openai.yaml`, `references/chrome_collection.md` and `references/schema.md`).

It sits in Backend & APIs, covering GraphQL, Frontend development and Social media marketing. It works with GraphQL and X (Twitter). The repository describes itself as: Open-source Codex skills from BGGG. The licence is MIT.

When your agent uses it

  • Social listening
  • Multilingual keyword discovery
  • Competitor monitoring
  • Historical search when X requires the users browser session and cookies

Example prompts

  • “s already logged-in Chrome, searching X”
  • “/bggg-data-x”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Use the Chrome plugin and follow its control skill. Select the user's Chrome explicitly, read its complete browser documentation, and…
  2. Open the first planned search URL. Confirm from visible page state that X is signed in and the search timeline is available. If sign-in…
  3. For each query, collect only rendered cards from the visible DOM. Follow references/chrome_collection.md for the exact selectors…
  4. Save one unmodified query package immediately after each query

What it can do on your machine

Read from SKILL.md and the folder at commit 1034ee5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Bggg Data X loads about 1.5k tokens when it runs, and up to ~3.4k if it reads all its reference files. Until then it costs about 162 tokens; SKILL.md has 573 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~162
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from binggandata/bggg-skills at commit 1034ee5, republished under its MIT licence (© binggandata). 573 words, ~1,546 tokens.

Download SKILL.mdSave it as .claude/skills/bggg-data-x/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
bggg-data-x
description
Collect auditable public X/Twitter posts by controlling the user's already logged-in Chrome, searching X's rendered web interface, scrolling visible results, and extracting original post text and metadata from DOM into normalized JSONL. Use for VOC research, social listening, multilingual keyword discovery, competitor monitoring, or historical search when X requires the user's browser session and cookies, credentials, internal GraphQL, paid APIs, or search-engine snippets must not be exported or used. X data layer of the bggg VOC suite (shared project folder; orchestrated by industry-orchestrator, reported by bggg-voc-report).

BGGG X Data

Collect public X posts from the visible, rendered search timeline in the user's logged-in Chrome. Preserve one source package per query, then normalize locally.

VOC Project Layout（bggg 系列共用）

bggg VOC 系列 skill（bggg-data-amazon / bggg-data-reddit / bggg-data-x / bggg-voc-report / industry-orchestrator）共用一个项目文件夹，让多平台数据规整到同一处、下游分析零改路径。开工先确定项目根目录 <project>（用户指定，或新建 voc-<产品或主题slug>/），并从 <project> 根目录执行本 skill 的全部命令（下文相对路径都基于它）：

text
<project>/
  PROJECT.md            # 研究简报 + 决策日志（编排 skill 维护；单独使用可省）
  config/               # 采集目标：amazon_targets.tsv / reddit_queries.tsv / x_queries.tsv / keywords.txt
  work/<platform>/…     # 各平台原始证据、attempt 日志、request plan、manifest
  data/raw/             # 各平台规范化 JSONL（统一行契约，分析共用层）
  data/clean|coded/     # 下游清洗与编码（industry-orchestrator 维护）
  output/               # 报告与交付物（bggg-voc-report 写 output/report/）

本 skill 的落点：config/x_queries.tsv → work/x/（request plan、逐查询 source package）→ data/raw/x_multi_<date>.jsonl。

Workflow

  1. Prepare a tab-separated query file:
text
query	lang	round	max_rows	sort
sample-ingredient lang:en	EN	1	250	latest
ボリュフィリン	JP	1	200	latest

Build a deterministic plan:

bash
python3 scripts/build_query_plan.py \
  --queries config/x_queries.tsv \
  --output work/x/request_plan.json

  1. Use the Chrome plugin and follow its control skill. Select the user's Chrome explicitly, read its complete browser documentation, and reuse the browser binding. Never inspect or export cookies, local storage, profiles, passwords, or session stores.

  2. Open the first planned search URL. Confirm from visible page state that X is signed in and the search timeline is available. If sign-in blocks the page, ask the user to sign in in Chrome; do not switch browser or bypass authentication.

  3. For each query, collect only rendered cards from the visible DOM. Follow references/chrome_collection.md for the exact selectors, extraction function, scroll loop, checkpointing, and failure handling.

  4. Save one unmodified query package immediately after each query:

text
work/x/source_json/001_EN.json
work/x/source_json/002_JP.json

Do not postpone all writes until the end of the run.

  1. Normalize and validate:
bash
python3 scripts/normalize_x_dom.py \
  --inputs work/x/source_json/*.json \
  --output data/raw/x_multi_2026-07-26.jsonl \
  --summary work/x/normalize_summary.json \
  --keywords keywords.txt
  1. Report query hits, unique Tweet IDs, rows by language, missing-text/date/URL counts, duplicate observations, failure reasons, earliest/latest date, and collection limitations.

Required DOM Contract

Use these selectors only against rendered page content:

text
post card          article[data-testid="tweet"]
post text          [data-testid="tweetText"]
author block       [data-testid="User-Name"]
canonical link     time[datetime] inside a[href*="/status/"]
timestamp          time[datetime]
engagement         [role="group"][aria-label]

Validate the contract on the first query before scaling. If any required selector returns zero while the visible timeline contains posts, stop and inspect the current DOM rather than emitting empty success files.

Show full SKILL.md (313 more words)Show less

Quality and Safety Rules

  • Read visible DOM only. Do not intercept, call, or parse X's GraphQL/REST responses.
  • Do not read, export, or persist browser cookies, tokens, local storage, credentials, or profile data.
  • Preserve exact text_raw, Tweet ID, canonical URL, timestamp, author handle, engagement label, query, language hint, and collection time.
  • Treat X search as a visible sample, not a complete census. Record latest versus top, query syntax, date bounds, caps, and stopping reason.
  • Deduplicate by Tweet ID after preserving every query observation. Keep all matched queries and language hints in the normalized row.
  • Separate consumers, promoters, sponsored UGC, media, and brands before calculating VOC prevalence.
  • Prefer multiple narrow queries over one giant OR query. Split large historical searches by month or quarter.
  • Use one tab and sequential queries by default. Avoid parallel browser tabs on the same account.
  • Stop on challenge pages, suspicious-login prompts, rate limits, or repeated blank timelines. Record the failure and leave account recovery to the user.
  • Never post, like, follow, reply, bookmark, or change account settings.
  • Finalize every tab opened by the task.

Scale Guidance

  • Default per-query cap: 250 posts.
  • Scroll about 1,500 px, then wait 850–1,500 ms.
  • Stop after 6 consecutive scrolls without a new Tweet ID.
  • Also use a hard scroll cap, such as 180 iterations, to prevent runaway loops.
  • For prevalence estimates, disclose X's search visibility limit and the query/date slicing scheme.

Degradation

If the logged-in Chrome session is unavailable or X blocks search, preserve the query plan and failure log. Do not substitute Tavily or search-engine snippets for original post text. Such tools may discover candidate URLs, but every quote must be revalidated against the original X page before entering the corpus.

Resources

  • scripts/build_query_plan.py: validate queries and build encoded X search URLs.
  • scripts/normalize_x_dom.py: merge per-query packages, parse engagement, deduplicate, and emit normalized JSONL.
  • references/chrome_collection.md: Chrome extraction loop and checkpoint contract.
  • references/schema.md: source-package and normalized-row schemas.

© binggandata, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (scripts, references) in bggg-data-x of binggandata/bggg-skills.

  • SKILL.md
  • agents/openai.yaml
  • references/chrome_collection.md
  • references/schema.md
  • scripts/build_query_plan.py
  • scripts/normalize_x_dom.py

Open the folder on GitHubat commit 1034ee5

Compare with similar skills

Bggg Data X next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Bggg Data X compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Bggg Data X this skillbinggandata/bggg-skills605—~1.5kAutomated safety check: PassMIT
Yichen Bookmarks Exportmcncarl/yichen-skills4.4k—~1.1kAutomated safety check: PassCustom licence
Add Property Typeyontrack/yontrack102—~990Automated safety check: PassMIT
Moai Ref API Patternsmodu-ai/moai-adk1.2k—~1.9kAutomated safety check: PassApache-2.0
Twitter X HubOpenMinis/MinisSkills446—~2.9kAutomated safety check: PassMIT
Bankr ShopifyBankrBot/skills1.2k—~5.7kAutomated safety check: PassNone

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Works with

Categories

Questions about Bggg Data X

What does Bggg Data X do?

Collect auditable public X/Twitter posts by controlling the user's already logged-in Chrome, searching X's rendered web interface, scrolling visible results, and extracting original post text and…. Bggg Data X is an agent skill from binggandata/bggg-skills. Collect auditable public X/Twitter posts by controlling the user's already logged-in Chrome, searching X's rendered web interface, scrolling visible results, and extracting original post text and metadata from DOM into normalized JSONL.

When should I use Bggg Data X?

Bggg Data X fits situations like: social listening; multilingual keyword discovery; competitor monitoring; historical search when X requires the users browser session and cookies.

How do I install Bggg Data X in Claude Code?

Run `npx skills add binggandata/bggg-skills --skill bggg-data-x -a claude-code`. Or copy the skill folder (bggg-data-x in binggandata/bggg-skills) into .claude/skills/bggg-data-x in your project. Claude Code loads it when a task matches its description.

How do I install Bggg Data X in Codex?

Run `npx skills add binggandata/bggg-skills --skill bggg-data-x -a codex`. Or copy the skill folder (bggg-data-x in binggandata/bggg-skills) into .agents/skills/bggg-data-x in your project. Codex loads it when a task matches its description.

Can I use Bggg Data X in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add binggandata/bggg-skills --skill bggg-data-x -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/bggg-data-x, .gemini/skills/bggg-data-x, .github/skills/bggg-data-x and .opencode/skills/bggg-data-x in your project.

What does Bggg Data X need to run?

Going by SKILL.md and its folder, Bggg Data X needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Bggg Data X access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Bggg Data X safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Bggg Data X use?

Bggg Data X is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Bggg Data X use?

About 1.5k tokens (SKILL.md is roughly 6.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.9k tokens, read only when the agent opens those files.

What are the alternatives to Bggg Data X?

Skills that share tags, products or a category with Bggg Data X: Yichen Bookmarks Export (mcncarl/yichen-skills, 4.4k stars), Add Property Type (yontrack/yontrack, 102 stars), Moai Ref API Patterns (modu-ai/moai-adk, 1.2k stars) and Twitter X Hub (OpenMinis/MinisSkills, 446 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Bggg Data X?

binggandata (a GitHub user) maintains it in binggandata/bggg-skills, which has 605 GitHub stars. The repository holds 13 skills in this directory. The repository was last updated on August 13, 2026.

Source: binggandata/bggg-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.