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 jianshuo/claude-skills --skill wjs-x-increasing-followergit clone --depth 1 https://github.com/jianshuo/claude-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/jianshuo/claude-skills/wjs-x-increasing-follower)<a href="https://agentmods.dev/skills/jianshuo/claude-skills/wjs-x-increasing-follower"><img src="https://agentmods.dev/badge/skills/jianshuo/claude-skills/wjs-x-increasing-follower/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/jianshuo/claude-skills/wjs-x-increasing-follower"><img src="https://agentmods.dev/badge/skills/jianshuo/claude-skills/wjs-x-increasing-follower.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 | $0.00161 | $0.02459 |
| Opus 5 | $0.00081 | $0.01229 |
| Sonnet 5 | $0.00032 | $0.00492 |
| Haiku 4.5 | $0.00016 | $0.00246 |
Grade A, and why
wjs-x-increasing-follower 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 13d 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 — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.
wjs-x-increasing-follower
把「涨粉」当工程做：每个改动是一个带编号的实验，有假设、有目标指标、有 before（可回滚）、有判决。不靠感觉，靠数。
Core Principle
单账号没法做平行 A/B —— 只能做时间轴上的前后对比。 所以唯一可信的北极星指标是 转化率 = 新增关注 ÷ 主页访问（ratio）：它对爆款流量免疫。一条推爆了带来一堆访问，ratio 不一定动；但 bio 改好了，每个来访的人更愿意关注，ratio 一定动。
所以指标分层（每个 action 必须声明自己被哪个指标考核）：
| Action 类型 | 拨动的杠杆 | 用什么考核 |
|---|---|---|
| profile（bio / 名字 / 头像 / banner / 置顶 / URL / 地点） | 转化 | ratio（北极星，抗爆款） |
| posting（格式 / 钩子 / 频率 / thread vs 单条） | 触达 | profile visits + impressions（ratio 当护栏，别把转化拖垮） |
| engagement（回复 / 关注别人 / 互动） | 触达 | new follows + visits |
| timing（发布时间） | 触达 | profile visits |
诚实护栏（写死在 evaluate.py 里）： 用中位数不用均值（一天爆款骗不了判决）；够 7 天 / 够数据才下判决；同指标实验窗口重叠 → 打 confounded 标记；只给「方向性」结论，不号称因果。
回滚是一等公民。 每个 action 存了精确的 before 值，#N 永远能还原。判 ❌ rollback 先问王建硕，绝不静默改他的 bio。
数据从哪来（关键约束）
ratio 这个数 X API / xurl 拿不到 —— 只活在 Analytics 看板里。所以靠 CSV 导出：
打开 x.com/i/account_analytics → Overview → 右上角下载图标（7D/2W/4W/3M/1Y 想要哪段先选好）→ 导出 CSV → 丢进 inbox/（或直接给路径）。
When This Skill Fires
- 王建硕说「涨粉」「搞个 X 涨粉实验」「A/B 测一下我的 profile」「今天的涨粉检查」
- 跑
/wjs-x-increasing-follower - 设了
/schedule daily /wjs-x-increasing-follower（见末尾「每日检查」）
When NOT to use
- 只是要发一条推 →
/wjs-tweeting-from-articles或直接xurl post - 推广 skill →
/wjs-promoting-skills//publish-skill - 把文章分发到各平台 →
/wjs-syndicating-articles
Workflow
所有脚本在 scripts/，状态在 state/。先 cd 到 skill 目录。
Step 1 — 吃数据（CSV → daily.jsonl）
python3 scripts/ingest-csv.py /path/to/export.csv
脚本模糊匹配列名（Profile visits / New follows / Impressions / Followers），按日期 upsert，自动算 ratio。它会打印它认的列映射 —— 看一眼对不对，不对就 --visits-col "X" --follows-col "Y"。重跑更长的导出会覆盖重叠的天，安全。
Step 2 — 出 to-do（提实验）
看 state/daily.jsonl 现状，给王建硕一份带编号的实验菜单。每条必须有：category / title / hypothesis / metric。原则：
- 一次只让少数 profile 实验在跑（同指标重叠会互相污染读数）。
- 假设要可证伪：「concrete 一行证明比模糊 tagline 转化高」✅；「让 bio 更好」❌。
- profile 类先于 posting 类 —— 转化是地基，先把来访的人接住，再去放大流量。
入账（自动分配编号，别手改 jsonl）：
What ships with it
11 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.
- inbox/.gitignore 12 B
- scripts/_common.py 1.8 KB runs code
- scripts/daily-check.sh 1.1 KB runs code
- scripts/evaluate.py 6.6 KB runs code
- scripts/ingest-csv.py 4.7 KB runs code
- scripts/ledger.py 5.3 KB runs code
- scripts/scoreboard.py 4.7 KB runs code
- state/.gitignore 6 B
- state/actions.jsonl 3.0 KB
- state/daily.jsonl 45 KB
- state/SCOREBOARD.md 1.9 KB
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.
- 13d ago First seen · 156 lines · 161 tokens per session scan A b91dd45f1c8c
wjs-x-increasing-follower is a skill published in the GitHub repository jianshuo/claude-skills (129 stars, last pushed 23d ago), licensed MIT. It adds 161 tokens to every session and 2,459 once invoked, about $0.0008 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 2026-08-30.
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