cheat-on-content
给所有想把"感觉"变成可校准预测的内容创作者。**方法论通用**——打分 → 盲预测 → T+3d 复盘 → 进化 rubric 的循环适用任何能被量化(播放 / 阅读 / 收听 / 点击)的内容。**rubric 是循环的内容,不是循环本身**——当前内置一份观点视频 rubric(参考博主 25+…
Audit a live page for accessibility issues, locate each WCAG violation precisely, and return a selector-grounded fix worklist without editing.
$ npx -y skills add LiHongwei-cn/lihongwei-cn --skill accesslint-scan --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/accesslint-scanContext preview
The summary Claude sees to decide when to auto-load this skill.
Audit a live page for accessibility issues, locate each WCAG violation precisely, and return a selector-grounded fix worklist without editing.
name: accesslint-scan description: "Audit a live page for accessibility issues, locate each WCAG violation precisely, and return a selector-grounded fix worklist without editing." risk: safe source: "https://github.com/AccessLint/skills" date_added: "2026-06-02"
Audit a live page and report what's broken and where. Locate; don't fix. If no URL in `$ARGUMENTS`, ask for one.
PORT=$(npx -y @accesslint/chrome@latest ensure | node -e 'process.stdin.on("data",d=>process.stdout.write(""+JSON.parse(d).port))')
npx -y @accesslint/cli@latest "<url>" --port "$PORT" --format jsonFlags as needed: `--selector`, `--wait-for "<selector>"`, `--include-aaa`, `--disable <rules>`.
Counts by impact, then one entry per violation:
Don't edit. For fixes: apply mechanical ones then re-run to verify; for bulk work hand off to `accesslint:audit`.
npx -y @accesslint/chrome@latest stop --all # skip if ensure reported "managed":false
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Repo: LiHongwei-cn/lihongwei-cn
给所有想把"感觉"变成可校准预测的内容创作者。**方法论通用**——打分 → 盲预测 → T+3d 复盘 → 进化 rubric 的循环适用任何能被量化(播放 / 阅读 / 收听 / 点击)的内容。**rubric 是循环的内容,不是循环本身**——当前内置一份观点视频 rubric(参考博主 25+…
提议并执行 rubric 或 bucket 升级。两种模式:**完整 rubric bump**(最高风险动作,5 步强制 + 跨模型审核)和 **--bucket-only 轻量重校**(只换 bucket 边界,不动 rubric 公式)。**Phase 2 强制走 cheat-score-blind…
cheat-on-content 的首次 onboarding 与脚手架创建器。统一流程——所有用户都走相同 5 阶段闭环,唯一区别是"发过视频的人"会在 init 时多一步:抓取已有视频建立历史 context(用于后续 cheat-seed 给更贴合的选题、更准的…
从对标账号导入 script + 数据 → 拆 pattern + 派生 base rubric 信号 → 写到 benchmark.md / script_patterns.md / rubric_notes.md。**这是工具最早期信号的来源**——cold-start…
把老用户的 .cheat-state.json 升级到当前 schema_version。读 migrations/registry.md 算迁移链,按顺序应用每一步迁移文件。幂等:跑两次结果一样。失败停在中间版本不前进。触发词:"迁移"/"升级 state"/"migrate"/"我的 state…
从复盘评论数据派生 / 刷新账号的受众画像,写入 audience.md。这是和 rubric 平行的第二个派生物——rubric 答"怎么打分",persona 答"谁在看"。cheat-seed 选题 / 写稿时读它。**audience.md 含实绩信号,cheat-score-blind…