Odalric — AI Research Engineer AI Skill
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Turn research into product: reproduce honestly, run real baselines and seeds, and kill what does not hold up.
- Critical paper reading and what will not reproduce at your scale
- Ablations, multiple seeds and honest significance testing
- Strong baselines, compute budgeting, hyperparameter strategy
- Benchmark contamination and the score-to-product-value gap
Applied research and ML teams deciding whether a promising paper deserves engineering time.An applied AI research engineer commands $180+/hr, this is one file, yours forever.
Drop Odalric into Claude and get a research engineer who runs multiple seeds and will tell you the paper's result did not reproduce at your scale.
Odalric turns papers into production systems: reading a paper critically and identifying what will not reproduce; reimplementation with an ablation plan; experiment design and tracking; statistical significance and why single-seed results mislead; baselines that are genuinely strong rather than strawmen; compute budgeting for research; distributed training basics; hyperparameter search strategy; reporting negative results honestly; benchmark contamination and leakage; the gap between benchmark score and product value; research-to-production handoff criteria; publishing and open-sourcing decisions; and keeping a research agenda tied to a product problem rather than to novelty.
What you get
- →Critical paper reading and what will not reproduce at your scale
- →Ablations, multiple seeds and honest significance testing
- →Strong baselines, compute budgeting, hyperparameter strategy
- →Benchmark contamination and the score-to-product-value gap
How to install
Download the .skill package → open Claude → paste SKILL.md into your Project Instructions or system prompt → describe your requirement → Odalric builds the answer. Includes a full worked example so you see exactly what you get.
# Odalric - AI Research Engineer You are Odalric, an applied AI research engineer. A single-seed result is an anecdote, and a weak baseline is a way of lying to yourself. ## How you work 1. Read the paper for what will not transfer before reimplementing 2. Build a genuinely strong baseline first 3. Run multiple seeds; report intervals, not a single number 4. Check for contamination; report negative results in full Never report a result you cannot reproduce across seeds, and kill a workstream openly when the evidence stops supporting it.
Excerpt from the actual file you'll download.
Four steps. Any AI chat.
- 01Download the file
After checkout, the download link lands in your inbox. Save the file anywhere on your device.
- 02Open your AI chat
Claude, ChatGPT, Gemini, Grok, or Copilot — whichever one you already use.
- 03Paste the file contents
Drop it into the system prompt, Project instructions, or custom instructions field.
- 04Start working
Your AI is now configured as a specialist. Ask it anything inside its domain.
No technical knowledge required. No subscription. Pay once, keep forever.
Works with every major AI chat.
Drop the file into your AI's system prompt, Project instructions, or custom instructions. No setup. No code. No vendor lock-in.
- Claude
- ChatGPT
- Gemini
- Grok
- Copilot
Works with any AI chat that accepts a system prompt or custom instructions.
Ready to specialise your AI?
One drop-in file. Pay once, keep forever — works with Claude & ChatGPT.