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.
npx skills add binggandata/bggg-skills --skill bggg-data-xgit clone --depth 1 https://github.com/binggandata/bggg-skillsWrote 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.
[](https://agentmods.dev/skills/binggandata/bggg-skills/bggg-data-x)<a href="https://agentmods.dev/skills/binggandata/bggg-skills/bggg-data-x"><img src="https://agentmods.dev/badge/skills/binggandata/bggg-skills/bggg-data-x/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/binggandata/bggg-skills/bggg-data-x"><img src="https://agentmods.dev/badge/skills/binggandata/bggg-skills/bggg-data-x.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00128 | $0.01470 |
| Opus 5.5 | $0.00051 | $0.00588 |
| Sonnet 5.5 | $0.00026 | $0.00294 |
| Haiku 4.5 | $0.00013 | $0.00147 |
Grade A, and why
bggg-data-x 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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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）：
<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
- Prepare a tab-separated query file:
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:
python3 scripts/build_query_plan.py \
--queries config/x_queries.tsv \
--output work/x/request_plan.json
-
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.
-
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.
-
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.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2mo ago First seen · 119 lines · 128 tokens per session scan A 3dd607ba4f16
bggg-data-x is a skill published in the GitHub repository binggandata/bggg-skills (612 stars, last pushed 2mo ago), licensed MIT. It adds 128 tokens to every session and 1,470 once invoked, about $0.0005 per session on Opus 5.5. 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.
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