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---
-name: conversion-architecture
-description: Design PDFtoMD conversion architecture, parser boundaries, internal block models, chunk policy, renderer contracts, output structure, logging, and resume behavior. Use when planning or reviewing conversion engine design.
---
-
-# Conversion Architecture
-
-## Workflow
-
-1. Read `AGENTS.md`, `PLAN.md`, `PROGRESS.md`, `docs/ARCHITECTURE.md`, `docs/CONVERSION_POLICY.md`, and `docs/ADR.md`.
-2. Keep responsibilities stable:
-   - Marker: layout, OCR, reading order, body, headings, tables, figures, captions
-   - Nougat: formula-only LaTeX parsing
-   - PyMuPDF: page pre-analysis, text-layer quality, page counts, chunk planning
-3. Define interfaces and invariants before implementation.
-4. Keep output deterministic and chunked under the documented output contract.
-5. Record architecture changes in `docs/ADR.md` when decisions change.
-
-## Guardrails
-
- Do not place conversion logic in a future PyQt UI.
- Do not add document sidecars unless explicitly requested.
- Do not let chunking split a paragraph, table, figure, or formula without a fallback plan.
@@ -1,4 +0,0 @@
-interface:
-  display_name: "Conversion Architecture"
-  short_description: "Plan parser and renderer boundaries"
-  default_prompt: "Use $conversion-architecture to design the next PDFtoMD engine phase."
@@ -1,24 +0,0 @@
---
-name: formula-quality
-description: Plan and review formula extraction quality for PDFtoMD. Use when Codex needs Nougat handoff rules, inline/block formula classification, LaTeX delimiter checks, equation numbering, reference anchors, or Marker fallback behavior.
---
-
-# Formula Quality
-
-## Workflow
-
-1. Read `AGENTS.md`, `docs/CONVERSION_POLICY.md`, `docs/TOOLCHAIN.md`, and `docs/ADR.md`.
-2. Identify formula candidates from Marker equation blocks or mathematical text patterns.
-3. Classify formulas as inline or block based on layout context.
-4. Validate:
-   - `$ ... $` and `$$ ... $$` balance
-   - `\begin{...}` / `\end{...}` pairs
-   - formula numbering
-   - body references such as `Eq. (3)` or Korean equation references
-5. Use Marker source text as fallback when Nougat fails.
-
-## Guardrails
-
- Do not pass whole documents through Nougat as the primary parser.
- Do not discard formula text on parse failure.
- Do not rewrite references as links unless the target confidence is sufficient.
@@ -1,4 +0,0 @@
-interface:
-  display_name: "Formula Quality"
-  short_description: "Validate equations and LaTeX output"
-  default_prompt: "Use $formula-quality to design formula parsing tests and fallback behavior."
@@ -1,27 +0,0 @@
---
-name: markdown-quality
-description: Plan and review Markdown output quality for PDFtoMD. Use when Codex needs tests or policies for headings, tables, HTML fallback, image links, captions, frontmatter, chunk integrity, and deterministic output.
---
-
-# Markdown Quality
-
-## Workflow
-
-1. Read `AGENTS.md`, `docs/PRD.md`, `docs/ARCHITECTURE.md`, and `docs/CONVERSION_POLICY.md`.
-2. Prefer focused assertions over full snapshots.
-3. Validate:
-   - heading hierarchy
-   - table parseability
-   - limited HTML table fallback
-   - image link existence
-   - figure/table captions
-   - internal references
-   - chunk frontmatter
-   - deterministic filenames and anchors
-4. Use Markdown or HTML parsers when practical.
-
-## Guardrails
-
- Do not inject runtime warnings into generated Markdown.
- Do not rely only on brittle whole-file snapshots.
- Do not lose complex table content without linking a fallback asset.
@@ -1,4 +0,0 @@
-interface:
-  display_name: "Markdown Quality"
-  short_description: "Check chunk Markdown and assets"
-  default_prompt: "Use $markdown-quality to plan focused Markdown output validation."
@@ -1,23 +0,0 @@
---
-name: pdf-toolchain
-description: Research and maintain PDFtoMD toolchain compatibility for Marker, Nougat, PyMuPDF, PyTorch/CUDA, model cache, and licensing. Use when Codex needs dependency pins, runtime compatibility checks, official-source research, or updates to docs/TOOLCHAIN.md and related ADRs.
---
-
-# PDF Toolchain
-
-## Workflow
-
-1. Read `AGENTS.md`, `PLAN.md`, `PROGRESS.md`, `docs/TOOLCHAIN.md`, `docs/ARCHITECTURE.md`, and `docs/ADR.md`.
-2. Prefer official or primary sources for current facts.
-3. Verify local facts with commands when relevant:
-   - `.\venv\python.exe -m pip check`
-   - `.\venv\python.exe -c "import torch; print(torch.__version__, torch.version.cuda, torch.cuda.is_available())"`
-   - `.\venv\Scripts\nougat.exe --help`
-4. Preserve the verified GTX 1070 Ti baseline unless a replacement is tested.
-5. Update `docs/TOOLCHAIN.md` and `docs/ADR.md` when dependency decisions change.
-
-## Guardrails
-
- Do not upgrade `torch`, `transformers`, `albumentations`, `pypdfium2`, `opencv-python-headless`, `Pillow`, or `fsspec` without re-running compatibility checks.
- Do not switch the primary parser away from Marker without an ADR update.
- Do not download model weights unless the user explicitly asks.
@@ -1,4 +0,0 @@
-interface:
-  display_name: "PDF Toolchain"
-  short_description: "PDF parser and CUDA dependency guidance"
-  default_prompt: "Use $pdf-toolchain to verify PDFtoMD dependency compatibility and update toolchain notes."
@@ -1,27 +0,0 @@
---
-name: sample-corpus
-description: Analyze and maintain the PDFtoMD samples corpus. Use when Codex needs to classify samples/ PDFs, design samples/metadata.json, identify OCR candidates, or connect corpus traits to focused regression tests.
---
-
-# Sample Corpus
-
-## Workflow
-
-1. Read `AGENTS.md`, `PLAN.md`, `PROGRESS.md`, `docs/PRD.md`, and `docs/CONVERSION_POLICY.md`.
-2. Inspect PDFs with PyMuPDF before proposing tests.
-3. Track these traits per PDF:
-   - page count
-   - text-layer quality
-   - scanned or mixed pages
-   - multi-column layout
-   - formula density
-   - table density
-   - figure density
-   - Korean filename/path coverage
-4. If writing metadata, use `samples/metadata.json` and update `PROGRESS.md`.
-
-## Guardrails
-
- Preserve original sample PDFs.
- Do not rename Korean sample files unless the user explicitly asks.
- Do not treat first-page text length as the only OCR signal.
@@ -1,4 +0,0 @@
-interface:
-  display_name: "Sample Corpus"
-  short_description: "Classify PDF samples for quality tests"
-  default_prompt: "Use $sample-corpus to audit samples/ PDFs and propose regression metadata."
@@ -1,23 +0,0 @@
---
-name: windows-runtime
-description: Maintain Windows-native PDFtoMD runtime behavior. Use when Codex needs guidance for repo-local venv, CUDA/OOM handling, Korean paths, long paths, model cache, offline operation, stderr logs, or resume cache behavior.
---
-
-# Windows Runtime
-
-## Workflow
-
-1. Read `AGENTS.md`, `docs/TOOLCHAIN.md`, `docs/ARCHITECTURE.md`, and `docs/CONVERSION_POLICY.md`.
-2. Verify environment health with:
-   - `.\venv\python.exe -m pip check`
-   - CUDA smoke test
-   - `.\venv\Scripts\nougat.exe --help`
-3. Use `pathlib` for path design and tests.
-4. Include Korean filenames, spaces, and long Windows paths in test plans.
-5. Keep model cache and offline behavior explicit.
-
-## Guardrails
-
- Do not silently fall back to CPU when the user explicitly requested CUDA.
- Do not choose batch sizes that assume more than 8 GB VRAM.
- Do not delete local environments or sample PDFs without explicit approval.
@@ -1,4 +0,0 @@
-interface:
-  display_name: "Windows Runtime"
-  short_description: "Windows, CUDA, paths, and offline checks"
-  default_prompt: "Use $windows-runtime to verify PDFtoMD local runtime assumptions."