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+…
Use when converting a PDF into another format such as Markdown, HTML, text, JSON, DOCX, or structured notes and the agent must choose the best extraction route, settings, and cleanup strategy for maximum fidelity and readability.
$ npx -y skills add LiHongwei-cn/lihongwei-cn --skill pdf-conversion-router --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/pdf-conversion-routerContext preview
The summary Claude sees to decide when to auto-load this skill.
Use when converting a PDF into another format such as Markdown, HTML, text, JSON, DOCX, or structured notes and the agent must choose the best extraction route, settings, and cleanup strategy for maximum fidelity and readability.
name: pdf-conversion-router description: Use when converting a PDF into another format such as Markdown, HTML, text, JSON, DOCX, or structured notes and the agent must choose the best extraction route, settings, and cleanup strategy for maximum fidelity and readability. risk: safe source: community date_added: "2026-05-23" metadata: category: technique triggers: pdf conversion, convert pdf, pdf to markdown, pdf to html, pdf to text, pdf to json, pdf to docx, OCR pdf, slide deck pdf, medical pdf, scanned pdf
Route every PDF conversion through a short analysis step before choosing tools or CLI flags.
The goal is not "extract the most text". The goal is:
Never start with one fixed default pipeline.
Always: 1. classify the PDF 2. classify the target output 3. choose the strongest route for that combination 4. validate the result on representative sections 5. if needed, retry with better settings before delivering
Heuristics are starting points, not guarantees.
Do not promote one flag combination into a universal default just because it worked well on one PDF. Prefer document-specific evidence over habit.
Use `opendataloader-pdf` as the primary conversion engine for every PDF conversion task by default.
This skill should assume:
Use other tools only for one of these reasons:
Identify the document class as quickly as possible:
Useful fast checks:
pdfinfo input.pdf pdftotext -layout input.pdf -
If text is missing or very poor, treat OCR as required.
Use these as default starting points:
`markdown-with-html + --table-method cluster + --image-output off`
`markdown-with-html + --image-output off` add `--table-method cluster` only if the default route under-structures important tabular content if tables are visually obvious but missing or badly fused, treat this as a detection problem, not a Markdown formatting problem if the selected route already reconstructs a real table but clips leading characters at column boundaries, treat that as a boundary-splitting defect, not a missing-table failure
start with `markdown` or `text` use `markdown-with-html` only if structure clearly matters
start with `markdown-with-html` add `--table-method cluster` when rows or columns flatten
OCR first, then convert with `opendataloader-pdf`
prefer `markdown-with-html` validate one easy section and one hard section before accepting output
Pick the output that best matches the document and the user's goal.
Use by default when the user wants Markdown and fidelity matters. Prefer this for tables, medical reports, slides, mixed-layout PDFs, and anything likely to break in pure Markdown.
Use only when clean plain Markdown matters more than layout fidelity.
Use when visual structure matters more than LLM readability.
Use for quick linear extraction, narrative documents, or when structure is unimportant.
Use when downstream machine processing matters more than human readability.
Use when the user wants editable office output and layout reconstruction matters.
Use OpenDataLoader as the default route.
Preferred defaults:
`-f markdown-with-html`
add `--table-method cluster`
add `--table-method cluster`
start without `--table-method cluster` add it only after a structure check shows meaningful improvement if a pseudo-table is already collapsed inside one detected row, changing only the Markdown flavor usually will not fix it if the active engine build recovers the pseudo-table structure, prefer fixing residual boundary artifacts before escalating to hybrid/full mode
add `--image-output off`
prefer validating both the command success and the actual rendered structure
validate key sections after conversion instead of trusting first pass
Default route:
opendataloader-pdf -f markdown-with-html --table-method cluster --image-output off
Then verify:
If a clinical table is flatten
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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…