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 PNGTRID/AnvilWiki --skill anvil-find-keywordsgit clone --depth 1 https://github.com/PNGTRID/AnvilWikiWrote 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/pngtrid/anvilwiki/anvil-find-keywords)<a href="https://agentmods.dev/skills/pngtrid/anvilwiki/anvil-find-keywords"><img src="https://agentmods.dev/badge/skills/pngtrid/anvilwiki/anvil-find-keywords/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/pngtrid/anvilwiki/anvil-find-keywords"><img src="https://agentmods.dev/badge/skills/pngtrid/anvilwiki/anvil-find-keywords.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 | $0.00110 | $0.03542 |
| Opus 5 | $0.00055 | $0.01771 |
| Sonnet 5 | $0.00022 | $0.00708 |
| Haiku 4.5 | $0.00011 | $0.00354 |
Grade A, and why
anvil-find-keywords 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 yesterday.
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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AnvilWiki 挖词选品（自动找词）
给「下一个站做哪个游戏」这个问题供弹药：多渠道挖候选 → 逐个快验 → 判决打分 → 落盘决策管理表。只读研究技能——不改任何代码与内容文件，只写 seo-reports/ 下的报告（该目录已 gitignore）。
方法论来源（先读再动手，本文件是它们的可执行版）：
docs/sourcing.md— 9 个挖词渠道 + 意图满足度 + 判决框架（打分表 / KD 分档 / 早期爆发轨 / 两判据 / 复查节奏）docs/game-selection.md— 四层漏斗（候选定级后的终审，在本技能之外）docs/handbook/zh/find-candidates.md— 「每天 20 分钟填候选池」的人工节奏（本技能是它的自动化版；英文版docs/handbook/en/find-candidates.md）
红线（违反即报告作废）
- 禁止编造数据。搜索量 / KD / 在线人数 / 播放量，任何查不到的数字一律标「未测」并写明原因——不许估算，不许拿印象充当数据，不许把旧数据当本周数据。
- 未测 ≠ 零。缺证据的项不计 0 分，最终建议必须点名哪些项是未测。「没测出机会」和「测出了没机会」是两句话。
- 平台内流量 ≠ 独立需求。聚合站推荐位、TikTok 播放量只证明平台愿意推；只有平台内信号的候选留在观察，除非 SERP / 搜索萌芽佐证。
- 分数是参考，拍板在用户。给出建议判级 + 证据链，不替用户把「做」写死；表格里【决定】列只写「建议：X」，由用户改定。
- 不覆盖用户结论。决策管理表里用户已填过「做 / 不做」的行，只追加复查记录，不推翻重写。
Step 0 — 输入收集（缺什么问什么，一次问完再开工）
- 目标市场（默认英语 / 美国——多数游戏词的最大盘）
- 已有站点与已判过「不做」的词（避免重复挖、避免撞自己的站）
- 有没有付费工具账号（Ahrefs / SEMrush / Similarweb）——有则解锁渠道 8 与搜量 / KD 实测
- 本轮预算（默认：一轮新增 3-5 个候选，宁缺毋滥）
新手提示：第一次挖词先按
docs/handbook/zh/find-candidates.md（03-05 课）人工跑一轮，建立判读手感再回到本技能提速——技能替你抓与算，判读的眼力来自人工那一轮。上一轮全军覆没的，先过「全军覆没排障」清单再开新轮。
Step 1 — 多渠道挖候选
渠道编号对齐 docs/sourcing.md 的 9 渠道；其中渠道 2（社媒）拆成 A2（Reddit，可抓）与 B1（TikTok / YouTube，登录墙）。优先跑 A 组，抓不到就换通道，不硬试也不空手而归。
A 组 · agent 自助通道（直接搜索 / 抓取）
| 渠道 | 怎么执行 |
|---|---|
| 1 · Steam 新游信号 | 🚨 steamdb.info 反爬严格，抓不到别硬试：换 steamcharts.com 抓近期上榜，或搜「trending steam games this week」类二手汇总。判据：玩家曲线最近几天才出现的才是真新游——发布日期会骗人（老游戏改名重发） |
| 2a · Reddit 异常值 | 抓 old.reddit.com 的 r/WebGames、r/incremental_games、r/playmygame 等版块：低赞账号的高互动帖、同一小游戏被多个账号自发提起 = 信号（抓不动就退回 site:reddit.com 搜索） |
| 3 · CrazyGames 新页 | 抓 crazygames.com/sitemap.xml 拉最新游戏页，逐个看玩过人数 / 评分 / 上线时间——两周以内、数据在涨、评分不差，记入候选 |
| 4 · Trends 飙升词 | 抓 Trends RSS：https://trends.google.com/trending/rss?geo=US（geo 换目标市场），从飙升词里筛游戏词；RSS 失效就搜「Google trending searches today」二手汇总 |
| 5 · 开发者 / 系列追更 | 用户有追更表就逐个查新作动态；没有就从本轮候选的开发商反查历史爆款与续作——过去产过爆款，新作起量有保底 |
| 6 · 经典爆款二创 | 对已知爆款搜「<游戏名> alternative / similar / like」，筛高热度平替新作；发现某老玩法还没有像样新作，本身就是选题；语言本地化空位（只有英文站的小众玩法）一并记下 |
| 7 · 预告游戏 | 搜近期游戏展新品汇总、Steam 愿望单榜新闻；预告期反应强烈的记入候选池分散下注（不重仓单一押注——开发解散 / 发布不及预期两种风险） |
| 9 · AI 类游戏 | 搜 AI dungeon alternatives、AI text adventure games 一类词——词新、站少、传统渠道覆盖不到 |
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.
- yesterday Changed · +13 lines b6892190a374
- 5d ago First seen · 101 lines · 110 tokens per session scan A a447709db50e
anvil-find-keywords is a skill published in the GitHub repository PNGTRID/AnvilWiki (137 stars, last pushed today), licensed MIT. It adds 110 tokens to every session and 3,542 once invoked, about $0.0006 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 2026-09-06.
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