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 skills add ConmuYan/my-academic-skills --skill research-codegit clone --depth 1 https://github.com/ConmuYan/my-academic-skillsWrote 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/conmuyan/my-academic-skills/research-code)<a href="https://agentmods.dev/skills/conmuyan/my-academic-skills/research-code"><img src="https://agentmods.dev/badge/skills/conmuyan/my-academic-skills/research-code/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/conmuyan/my-academic-skills/research-code"><img src="https://agentmods.dev/badge/skills/conmuyan/my-academic-skills/research-code.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00121 | $0.02318 |
| Opus 5 | $0.00060 | $0.01159 |
| Sonnet 5 | $0.00024 | $0.00464 |
| Haiku 4.5 | $0.00012 | $0.00232 |
Grade A, and why
research-code 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 10d ago.
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.
How it starts
The opening of the file, as written. The whole thing — 241 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Code
You are writing paper prototype code for a university deep-learning lab, not a production system and not a framework.
Optimize for: the idea is correct; the code is short; a PhD student can
read forward, the loss, the batch, and the train loop in 10 minutes,
then change it, ablate it, and reproduce it.
Do not optimize for extensibility, plugins, audit, config platforms, error-recovery frameworks, or future-proof abstractions.
When to use
- Implement a paper method, baseline, or ablation
- 写论文代码 / 科研原型 / 顶会开源风格
- Existing code is over-engineered; user wants 去工程化 or a single file
- User is fighting factory / registry / hook / trainer / manager / audit code
When not to use
| Request | Do this instead |
|---|---|
| Web API, service, product backend | Ordinary software engineering |
| Docker / CI / packaging / docs site | Only if the user named that deliverable |
| MMDetection-style training framework | User must name that goal |
| Abstract / idea / novelty / English polish | awesome-abstract / idea-spark / scoop-check / nature-polishing |
Mode
| User signal | Mode |
|---|---|
| 实现 / implement / 按论文写 | implement |
| 去工程化 / 重构 / 删包装 | refactor |
| 压成单文件 / one file | compress |
| 检查是否过度工程化 / review | review |
| 写进仓库规则 / AGENTS.md / .cursorrules | repo-rules |
Default: implement if there is no code, refactor if they point at bloated code.
Hard rules
- Correctness of the research idea beats every style rule.
- Clarity beats abstraction. Prefer functions. A class is allowed only when
it is semantically required (
nn.Module, a real Dataset). - Default layout is four files. Do not invent a framework.
- Only the paper's new module is custom. Everything else is a library call.
- Map important forward/loss lines to equation numbers and tensor shapes.
- Expose only experiment knobs (dataset, lr, epochs, seed, hidden, dropout).
- Reproducibility floor: seed, device, printed metrics, optional best checkpoint.
- Never add a file, class, or directory "for later".
- If the plan exceeds the budget, cut first. Do not write the bloated version.
- After writing, run the checklist. A failed box is a bug; fix it before showing code.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 241 lines · 121 tokens per session scan A 556a5d4b12c4
research-code is a skill published in the GitHub repository ConmuYan/my-academic-skills (2 stars, last pushed 23d ago), licensed MIT. It adds 121 tokens to every session and 2,318 once invoked, about $0.0006 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 2026-08-31.
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