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 niuz257470-ctrl/natureskills --skill nature-polishinggit clone --depth 1 https://github.com/niuz257470-ctrl/natureskillsWrote 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/niuz257470-ctrl/natureskills/nature-polishing)<a href="https://agentmods.dev/skills/niuz257470-ctrl/natureskills/nature-polishing"><img src="https://agentmods.dev/badge/skills/niuz257470-ctrl/natureskills/nature-polishing/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/niuz257470-ctrl/natureskills/nature-polishing"><img src="https://agentmods.dev/badge/skills/niuz257470-ctrl/natureskills/nature-polishing.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 | $0.00080 | $0.02718 |
| Opus 5 | $0.00040 | $0.01359 |
| Sonnet 5 | $0.00016 | $0.00544 |
| Haiku 4.5 | $0.00008 | $0.00272 |
Grade A, and why
nature-polishing 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 11d 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.
This is a copy
92% identical to nature-polishing — 14 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 379 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Nature-Style Academic Polishing
Use this skill to improve scientific writing at two levels:
main strategy: paper architecture, section logic, reader workflow, evidence thresholds, and ethicsreference support: reusable phrase families, move patterns, transitions, and style checks
The main strategy should come from the course notes in Chapter1-Week1-7. The reference wording layer should come from Academic Phrasebank.
Default stance
- Language serves argument. Do not polish sentences while leaving the reasoning broken.
- Write with empathy for the reader: relevance first, then novelty, then trust, then reuse, then meaning.
- There should be no mystery for the writer, but there may be one for the reader.
- Do not invent data, references, mechanisms, or novelty claims.
- Do not let AI draft the paper's core scientific argument from scratch.
- If the draft is Chinese or structurally rough, reconstruct the logic first and the prose second.
- Avoid em dashes in polished output by default. Prefer commas, parentheses, or full stops. Use colons sparingly unless the user explicitly asks to preserve dash-based punctuation or wants a colon-led style.
When to open extra files
These files are reference support. Use them after the section's rhetorical job is clear.
| File | Open when |
|---|---|
| references/section-moves.md | You need section-specific move orders or phrase patterns derived from Academic Phrasebank |
| references/phrasebank-playbook.md | You need hedging, transition, evidence, limitation, or future-work phrase families |
| references/style-guardrails.md | You need academic-style checks, paragraph/sentence checks, article use, register, or mechanics |
Core architecture
1. Identify the paper type first
Before editing, determine what kind of paper or section this is.
Research paper: the reader asks why the phenomenon matters, what was done, what was found, and what it means.Methods paper: the reader asks whether the method works, whether it is reproducible, and whether it is better under a fair comparison.Hypothesis-based work: the argument tries to establish or rule out a causal explanation.Algorithmic or device work: the argument proposes a procedure, tool, or system and must show that it performs reliably and advantageously.
What ships with it
5 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.
- 11d ago First seen · 379 lines · 80 tokens per session scan A 9ad5e1f8ca7b
nature-polishing is a skill published in the GitHub repository niuz257470-ctrl/natureskills (61 stars, last pushed 4mo ago), licensed MIT. It adds 80 tokens to every session and 2,718 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to nature-polishing, differing in 14 lines, and is treated as a copy.
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