paper-to-engineering-features

name	paper-to-engineering-features
description	Transform HuggingFace/arXiv research papers into trainable engineering features, skills, scripts and configs for Qwen 3.5 0.8B. Use when user provides a paper URL or wants to convert research into implementation. Creates complete skill ecosystems with ASCII diagrams.

Paper to Engineering Features

Converts research papers into trainable engineering features for the TTC Stack.

Input

User provides a paper URL:

• HuggingFace Papers: https://huggingface.co/papers/<paper-id>
• arXiv: https://arxiv.org/abs/<paper-id>

Workflow

1. Fetch Paper

HuggingFace Papers:

PAPER_ID="<paper-id from URL>"
curl -s "https://huggingface.co/api/papers/$PAPER_ID"

arXiv:

PAPER_ID="<paper-id from URL>"
curl -s "http://export.arxiv.org/api/query?id_list=$PAPER_ID"

2. Extract Engineering Features

Category	What to Look For
Architecture	Layer modifications, attention variants, skip connections, MoE
Training	Loss functions, optimization, curriculum learning
Algorithms	Sampling strategies, routing logic, decoding
Data	Dataset requirements, preprocessing
Evaluation	Benchmarks, metrics, baselines

3. Map to TTC Stages

CPT (Continued Pre-Training)
├── Architecture changes → checkpoint surgery
└── Tokenizer changes → vocabulary expansion

SFT (Supervised Fine-Tuning)
├── Instruction format → chat template configs
└── Data requirements → dataset schemas

RLVR (Reinforcement Learning)
├── Reward signals → verifier configs
└── Policy updates → GRPO/DPO configs

TTC (Test-Time Compute)
├── Router decisions → router configs
└── Parallel sampling → best-of-N configs

4. Generate Skill Package

qwen-<feature-name>/
├── SKILL.md
├── scripts/
│   ├── train.py
│   ├── evaluate.py
│   └── inference.py
├── references/
│   ├── architecture.md
│   └── paper-summary.md
└── configs/
    ├── sft.yaml
    ├── rlvr.yaml
    └── router.yaml

5. Create ASCII Diagram

┌─────────────────────────────────────────────┐
│              Qwen 3.5 0.8B                  │
│  ┌─────────────────────────────────────┐   │
│  │        [Feature modifications]      │   │
│  └─────────────────────────────────────┘   │
└─────────────────────────────────────────────┘

6. Create GitHub Repos

gh repo create qwen-<feature-name> --public --description "Qwen implementation"
git init && git add . && git commit -m "Initial skill ecosystem"
git push origin main

Output

Provide:

1. Paper Summary (3 bullets)
2. Features Table
3. TTC Stage Mapping
4. Generated Skills (3-5 per paper)
5. ASCII Diagram
6. GitHub Repo Links
7. Installation Commands

Example

From https://huggingface.co/papers/2512.24880:

Skill	Purpose	Backend
qwen-mhc-architecture-lab	Architecture retrofit	Kaggle
qwen-mhc-kaggle-smoke	Quick validation	Kaggle
qwen-mhc-hf-jobs	Full training	HF Jobs
qwen-mhc-bridge	Pipeline bridge	N/A
qwen-mhc-retrofit-lab	Checkpoint surgery	Local