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 tuoxie2046/claude-code-research-skills --skill research-paper-writinggit clone --depth 1 https://github.com/tuoxie2046/claude-code-research-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/tuoxie2046/claude-code-research-skills/research-paper-writing)<a href="https://agentmods.dev/skills/tuoxie2046/claude-code-research-skills/research-paper-writing"><img src="https://agentmods.dev/badge/skills/tuoxie2046/claude-code-research-skills/research-paper-writing/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/tuoxie2046/claude-code-research-skills/research-paper-writing"><img src="https://agentmods.dev/badge/skills/tuoxie2046/claude-code-research-skills/research-paper-writing.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 | $0.00068 | $0.00991 |
| Opus 5 | $0.00034 | $0.00495 |
| Sonnet 5 | $0.00014 | $0.00198 |
| Haiku 4.5 | $0.00007 | $0.00099 |
Grade A, and why
research-paper-writing 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 9d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
What ships with it
38 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.
- agents/openai.yaml 243 B
- references/abstract.md 3.5 KB
- references/conclusion.md 1.2 KB
- references/does-my-writing-flow-source.md 4.9 KB
- references/examples/abstract-examples.md 875 B
- references/examples/abstract/template-a.md 950 B
- references/examples/abstract/template-b.md 3.2 KB
- references/examples/abstract/template-c.md 1.7 KB
- references/examples/index.md 2.3 KB
- references/examples/introduction-examples.md 1.5 KB
- references/examples/introduction/novel-task-challenge-decomposition.md 1.5 KB
- references/examples/introduction/pipeline-not-recommended-abstract-only.md 2.9 KB
- references/examples/introduction/pipeline-version-1-one-contribution-multi-advantages.md 2.0 KB
- references/examples/introduction/pipeline-version-2-two-contributions.md 2.0 KB
- references/examples/introduction/pipeline-version-3-new-module-on-existing-pipeline.md 1.5 KB
- references/examples/introduction/pipeline-version-4-observation-driven.md 1.4 KB
- references/examples/introduction/technical-challenge-version-1-existing-task.md 2.6 KB
- references/examples/introduction/technical-challenge-version-2-existing-task-insight-backed-by-traditional.md 3.8 KB
- references/examples/introduction/technical-challenge-version-3-novel-task.md 1.6 KB
- references/examples/introduction/version-1-task-then-application.md 727 B
- references/examples/introduction/version-2-application-first.md 405 B
- references/examples/introduction/version-3-general-to-specific-setting.md 847 B
- references/examples/introduction/version-4-open-with-challenge.md 1.7 KB
- references/examples/method-examples.md 1.0 KB
- references/examples/method/example-of-the-three-elements.md 7.3 KB
- references/examples/method/method-writing-common-issues-note.md 355 B
- references/examples/method/module-design-instant-ngp.md 4.5 KB
- references/examples/method/module-motivation-patterns.md 410 B
- references/examples/method/module-triad-neural-body.md 763 B
- references/examples/method/neural-body-annotated-figure-text.md 2.8 KB
- references/examples/method/overview-template.md 2.0 KB
- references/examples/method/pre-writing-questions.md 479 B
- references/examples/method/section-skeleton.md 110 B
- references/experiments.md 4.4 KB
- references/introduction.md 15 KB
- references/method.md 6.1 KB
- references/paper-review.md 5.3 KB
- references/related-work.md 1.3 KB
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.
- 9d ago First seen · 100 lines · 68 tokens per session scan A 1d55abfeb520
research-paper-writing is a skill published in the GitHub repository tuoxie2046/claude-code-research-skills (5 stars, last pushed 2mo ago), with no licence file. It adds 68 tokens to every session and 991 once invoked, about $0.0003 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
food-research
Run a comprehensive, multi-source literature and evidence-synthesis workflow for food & nutrition science. Use when the user wants to research a food/nutrition topic in depth, do a literature review, build an evidence brief, screen and synthesize many sources, verify citations, or scope a systematic review.…
food-paper
Multi-subagent manuscript system for food & nutrition science covering the whole research process: understand the field, frame research questions, curate and analyze data, run statistics, build figures and tables, construct the discussion, draft, polish, and self-review — journal-aware throughout. Includes a…
food-pipeline
Master orchestrator for the whole food & nutrition research-to-publication workflow. Coordinates the specialist skills — each with its own subagent set — into one governed path: journal selection, research (food-research / food-deep-research), writing & analysis (food-paper), figures (food-figure), peer review…
food-deep-research
General-purpose deep research that produces a fully written, source-validated literature review on any question: scope it, design the method, discover and screen sources by journal ranking, validate every source, extract and verify evidence, synthesize, stress-test, then write and format the review (APA 7.0 by…
food-figure
Comprehensive figure system for food & nutrition manuscripts: analyzes the user's data, recommends the best figure(s) to make, then produces submission-grade graphics in Python or R at the target journal's spec. Handles all common scientific figure types (bar/box/violin, line/kinetic, scatter/regression, Bland–Altman…
food-review
Multi-reviewer peer-review system for food & nutrition manuscripts. Simulates an editorial panel — a coordinating editor, three domain reviewers (methodology/statistics, domain/novelty, integrity/ethics), and a devil's advocate — plus a formatting-compliance check against the target journal (APA 7.0 by default, or a…