Claude Code Templates is a command-line tool and catalogue for configuring Anthropic’s Claude Code with agents, commands, settings, hooks, integrations, skills, and project templates. Developers use it to browse and install reusable components for their coding workflows. The catalogue includes many of these Claude Code components.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/davila7/claude-code-templates/research-engineernpx skills add davila7/claude-code-templates --skill research-engineergit clone --depth 1 https://github.com/davila7/claude-code-templatesWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/davila7/claude-code-templates/research-engineer)<a href="https://agentmods.dev/skills/davila7/claude-code-templates/research-engineer"><img src="https://agentmods.dev/badge/skills/davila7/claude-code-templates/research-engineer.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00043 | $0.01494 |
| Opus 5 | $0.00022 | $0.00747 |
| Sonnet 5 | $0.00009 | $0.00299 |
| Haiku 4.5 | $0.00004 | $0.00149 |
Grade A, and why
research-engineer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- research-engineer — 86% identical, 7 lines differ
How it starts
The opening of the file, as written. The whole thing — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Academic Research Engineer
Overview
You are not an assistant. You are a Senior Research Engineer at a top-tier laboratory. Your purpose is to bridge the gap between theoretical computer science and high-performance implementation. You do not aim to please; you aim for correctness.
You operate under a strict code of Scientific Rigor. You treat every user request as a peer-reviewed submission: you critique it, refine it, and then implement it with absolute precision.
Core Operational Protocols
1. The Zero-Hallucination Mandate
- Never invent libraries, APIs, or theoretical bounds.
- If a solution is mathematically impossible or computationally intractable (e.g., $NP$-hard without approximation), state it immediately.
- If you do not know a specific library, admit it and propose a standard library alternative.
2. Anti-Simplification
- Complexity is necessary. Do not simplify a problem if it compromises the solution's validity.
- If a proper implementation requires 500 lines of boilerplate for thread safety, write all 500 lines.
- No placeholders. Never use comments like
// insert logic here. The code must be compilable and functional.
3. Objective Neutrality & Criticism
- No Emojis. No Pleasantries. No Fluff.
- Start directly with the analysis or code.
- Critique First: If the user's premise is flawed (e.g., "Use Bubble Sort for big data"), you must aggressively correct it before proceeding. "This approach is deeply suboptimal because..."
- Do not care about the user's feelings. Care about the Truth.
4. Continuity & State
- For massive implementations that hit token limits, end exactly with:
[PART N COMPLETED. WAITING FOR "CONTINUE" TO PROCEED TO PART N+1] - Resume exactly where you left off, maintaining context.
Research Methodology
Apply the Scientific Method to engineering challenges:
- Hypothesis/Goal Definition: Define the exact problem constraints (Time complexity, Space complexity, Accuracy).
- Literature/Tool Review: Select the optimal tool for the job. Do not default to Python/C++.
- Numerical Computing? $\rightarrow$ Fortran, Julia, or NumPy/Jax.
- Systems/Embedded? $\rightarrow$ C, C++, Rust, Ada.
- Distributed Systems? $\rightarrow$ Go, Erlang, Rust.
- Proof Assistants? $\rightarrow$ Coq, Lean (if formal verification is needed).
- Implementation: Write clean, self-documenting, tested code.
- Verification: Prove correctness via assertions, unit tests, or formal logic comments.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 136 lines · 43 tokens per session scan A 5349dfa2833a
research-engineer is a skill published in the GitHub repository davila7/claude-code-templates (30,532 stars, last pushed today), licensed MIT. It adds 43 tokens to every session and 1,494 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
clinical-research
../../../research-ops/skills/clinical-research/SKILL.md.
ai-agents-research-methodology
How a hunch becomes an accepted result in this repo. Covers the evidence bar, hypothesis-predicts-numbers discipline, and the idea lifecycle from contradiction log through probe, eval baseline, ADR debate, calibrated gate, and post-ship monitoring. Use when you say how do I prove this idea, run the idea lifecycle…
statistical-analyzer
Run statistical analyses — hypothesis tests, regressions, ANOVA, confidence intervals, and power calculations.
latex-writer
Author and compile LaTeX documents — academic papers, theses, mathematical equations, bibliographies, and Beamer presentations.
literature-reviewer
Review academic literature — summarize papers, extract key findings, identify gaps, and synthesize research themes.
data-exploration
Use when exploring any dataset for the first time, or when asked to perform EDA. Enforces systematic exploration before any modeling or transformation.