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 Yila-AI/awesome-research-skills --skill science-research-writinggit clone --depth 1 https://github.com/Yila-AI/awesome-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/yila-ai/awesome-research-skills/science-research-writing)<a href="https://agentmods.dev/skills/yila-ai/awesome-research-skills/science-research-writing"><img src="https://agentmods.dev/badge/skills/yila-ai/awesome-research-skills/science-research-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/yila-ai/awesome-research-skills/science-research-writing"><img src="https://agentmods.dev/badge/skills/yila-ai/awesome-research-skills/science-research-writing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 28 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00054 | $0.01578 |
| Opus 5 | $0.00027 | $0.00789 |
| Sonnet 5 | $0.00011 | $0.00316 |
| Haiku 4.5 | $0.00005 | $0.00158 |
Grade A, and why
science-research-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 7d 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 — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Science Research Writing
Turn the author's research materials into the next useful manuscript deliverable. Guide the writing process without replacing scientific judgment or inventing intellectual content.
Load only what is needed
- Always read
references/input-output-contract.mdandreferences/certainty-and-claim-strength.md. - Read
references/reverse-engineering-protocol.mdwhen target papers are supplied or the user requests journal adaptation. - Read only the relevant section reference:
introduction.md,methods.md,results.md,discussion.md,conclusion.md,abstract.md, ortitle.md. - Use
assets/section-function-map.mdfor planning,assets/evidence-ledger.csvfor provenance-sensitive drafting, andassets/target-journal-model.jsonfor target-paper modeling.
First response: inspect before asking
Read all supplied materials first. Identify:
- manuscript stage: idea, research materials, partial draft, or full draft;
- primary job:
lookup,learn,model,plan,draft,revise, oraudit; - paper section and empirical design when inferable;
- facts, numbers, citations, technical terms, null findings, limitations, and author judgments that must be protected;
- the next useful output that can be produced safely now.
Do not ask the user to choose an internal mode. Do not require field, journal, section, or language preferences when a conservative useful result is possible.
If missing information would force an unsupported scientific choice:
- deliver every safe and useful part first;
- identify the exact gap or conflict;
- ask one highest-impact question;
- wait before drafting only the blocked content.
If conflicting sources block the entire requested sentence or section, return a diagnosis rather than a provisional scaffold. Do not infer variable roles, direction, reference groups, statistical meaning, table labels, or missing uncertainty from the conflicting numbers.
Route the task
Idea stage
Use plan. Convert the question and intended contribution into a provisional section-function map. Label missing evidence instead of supplying it.
What ships with it
16 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 245 B
- assets/evidence-ledger.csv 76 B
- assets/section-function-map.md 668 B
- assets/target-journal-model.json 130 B
- references/abstract.md 1.5 KB
- references/certainty-and-claim-strength.md 2.3 KB
- references/conclusion.md 1.4 KB
- references/discussion.md 2.8 KB
- references/input-output-contract.md 3.7 KB
- references/introduction.md 1.8 KB
- references/methods.md 1.7 KB
- references/results.md 1.8 KB
- references/reverse-engineering-protocol.md 2.9 KB
- references/title.md 1.4 KB
- scripts/check_draft_invariants.py 4.5 KB runs code
- scripts/validate_writing_model.py 3.5 KB runs code
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.
- 7d ago Changed · +1 lines 6fcd871bcaa3
- 13d ago First seen · 132 lines · 54 tokens per session scan A 433d83823cc1
science-research-writing is a skill published in the GitHub repository Yila-AI/awesome-research-skills (119 stars, last pushed 8d ago), licensed Apache-2.0. It adds 54 tokens to every session and 1,578 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 2026-08-30.
Other skills, from other repositories
systems-paper-writing
Comprehensive guide for writing systems papers targeting OSDI, SOSP, ASPLOS, NSDI, and EuroSys. Provides paragraph-level structural blueprints, writing patterns, venue-specific checklists, reviewer guidelines, LaTeX templates, and conference deadlines. Use this skill for all systems conference paper writing.
arxiv-search
Search arXiv physics, math, and computer science preprints using natural language queries. Powered by Valyu semantic search.
proof-checker
A mathematical proof review and repair workflow for LaTeX documents. It checks whether a proof has valid reasoning, addresses identified gaps, reviews the fixes, and produces an audit report.
paper-illustration
A workflow for generating academic illustrations, such as architecture diagrams and method visuals, with image generation and repeated review. Claude plans and checks the figure during the process.
paper-illustration-image2
Generate publication-quality academic illustrations through a local Codex app-server bridge that uses Codex native image generation. This is a separate experimental alternative to paper-illustration, intended for Claude Code users who want a GPT-image-style renderer without modifying the original skill.
idea-discovery-robot
A robotics-focused workflow for turning a broad robotics or embodied-AI direction into ideas grounded in papers, benchmarks, and experiments. Embodied AI means artificial intelligence that acts through a physical or simulated robot.