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 fcakyon/phd-skills --skill research-publishinggit clone --depth 1 https://github.com/fcakyon/phd-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/fcakyon/phd-skills/research-publishing)<a href="https://agentmods.dev/skills/fcakyon/phd-skills/research-publishing"><img src="https://agentmods.dev/badge/skills/fcakyon/phd-skills/research-publishing/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/fcakyon/phd-skills/research-publishing"><img src="https://agentmods.dev/badge/skills/fcakyon/phd-skills/research-publishing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00064 | $0.00987 |
| Opus 5.5 | $0.00026 | $0.00395 |
| Sonnet 5.5 | $0.00013 | $0.00197 |
| Haiku 4.5 | $0.00006 | $0.00099 |
Grade A, and why
research-publishing 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 2mo 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Publishing Methodology
You are helping a researcher prepare their code and artifacts for public release alongside a paper submission.
Step 1: Repository Assessment
Before any changes, audit the current state:
-
Sensitive content scan:
- API keys, tokens, credentials (grep for common patterns)
- Hardcoded paths specific to the researcher's machine
- Internal URLs or private infrastructure references
- Personal identifiable information in comments or data
-
Dependency audit:
- List all dependencies with pinned versions
- Identify any proprietary or restricted-license dependencies
- Check for abandoned/unmaintained dependencies
- Verify all dependencies are pip/conda installable
-
Code organization:
- Identify dead code, debugging artifacts, scratch files
- Find duplicated code that should be unified
- Check for overly complex code that can be simplified
Step 2: Repository Structure
A publishable research repository should have:
project/
README.md # Installation, usage, citation
LICENSE # Must have an explicit license
requirements.txt # or pyproject.toml with pinned deps
setup.py / setup.cfg # Package installation
src/ # Source code
scripts/ # Training, evaluation, inference scripts
configs/ # Configuration files
data/ # Sample data or download instructions
checkpoints/ # Download instructions (not actual weights)
results/ # Key result files referenced in paper
Step 3: Reproducibility Checklist
For each experiment in the paper:
- Configuration file exists and matches paper's hyperparameters
- Random seeds are set and documented
- Training command is documented end-to-end
- Evaluation command produces the reported numbers
- Data preprocessing steps are scripted (not manual)
- Hardware requirements are documented (GPU type, memory, time)
- Dependencies are version-pinned
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.
- 2mo ago First seen · 122 lines · 64 tokens per session scan A ac298a042983
research-publishing is a skill published in the GitHub repository fcakyon/phd-skills (437 stars, last pushed 18d ago), licensed MIT. It adds 64 tokens to every session and 987 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-30.
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