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 yniantongtian-oss/nature-skills --skill nature-responsegit clone --depth 1 https://github.com/yniantongtian-oss/nature-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/yniantongtian-oss/nature-skills/nature-response)<a href="https://agentmods.dev/skills/yniantongtian-oss/nature-skills/nature-response"><img src="https://agentmods.dev/badge/skills/yniantongtian-oss/nature-skills/nature-response/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/yniantongtian-oss/nature-skills/nature-response"><img src="https://agentmods.dev/badge/skills/yniantongtian-oss/nature-skills/nature-response.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 | $0.00091 | $0.00869 |
| Opus 5 | $0.00046 | $0.00434 |
| Sonnet 5 | $0.00018 | $0.00174 |
| Haiku 4.5 | $0.00009 | $0.00087 |
Grade A, and why
nature-response 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 12d 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 — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Nature Reviewer Response — Router
This skill is split into two layers:
- A static layer under
static/that holds versioned, reusable content fragments (the default stance and red lines, and the response workflow with output format). - A dynamic layer (this file plus
manifest.yaml) that loads the core every time and reaches for the deeper response references only when a step needs them.
Do not try to apply the response logic from memory or from this router. Always load fragments from disk as described below.
Routing protocol
Follow these four steps every time the skill is invoked.
1. Load the manifest and the core layer
Read manifest.yaml. Then read every file listed under always_load:
static/core/stance.md— the editor-facing purpose, the default stance, the red lines, and the source hierarchy that apply to every response job.static/core/workflow.md— accepted inputs, the ten-step workflow, and the output package format.
2. No content axis — identify mode and language inline
Unlike nature-writing or nature-figure, nature-response has no fragment axis. Its variation is identified at runtime, not by loading different content bodies:
- task mode —
draft/audit/revise/triage-only/appeal-like. - decision type — minor revision, major revision, revise-and-resubmit, transfer after review, or unclear.
- user language — if the user writes Chinese, also produce the 中文核对 block.
Use references/intake-and-routing.md to fix the task mode, minimum inputs, and readiness state before drafting. Route appeal-like cases separately; do not draft an appeal as the default path.
3. Run the workflow
Follow the ten-step workflow in core/workflow.md: identify mode and decision type, extract editor instructions (IDs E.1) then reviewer comments (R1.1, R2.1), classify each item, build a strategy summary, draft point-by-point responses from the preserved comments, map every claimed change to a manuscript location or an explicit placeholder, flag missing author input, run QA, and return the package with a readiness state.
What ships with it
23 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.
- examples/conflicting-reviewers.md 1.4 KB
- examples/major-revision-with-missing-evidence.md 1.5 KB
- examples/minor-revision.md 1.7 KB
- manifest.yaml 2.1 KB
- README.md 4.7 KB
- references/action-mapping.md 3.6 KB
- references/chinese-author-alignment.md 3.3 KB
- references/comment-taxonomy.md 4.1 KB
- references/difficult-cases.md 4.0 KB
- references/intake-and-routing.md 4.9 KB
- references/qa-checklist.md 3.1 KB
- references/response-structure.md 3.5 KB
- references/source-basis.md 3.2 KB
- references/tone-and-stance.md 3.3 KB
- static/core/stance.md 2.4 KB
- static/core/workflow.md 2.0 KB
- tests/conflicting-reviewers.md 1.8 KB
- tests/defensive-draft-audit.md 1.7 KB
- tests/evaluation-summary.md 2.2 KB
- tests/impossible-experiment.md 1.6 KB
- tests/major-revision-missing-evidence.md 1.8 KB
- tests/minor-revision.md 1.4 KB
- tests/rubric.md 2.6 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.
- 12d ago First seen · 60 lines · 91 tokens per session scan A c00037479e44
nature-response is a skill published in the GitHub repository yniantongtian-oss/nature-skills (24 stars, last pushed 3mo ago), licensed MIT. It adds 91 tokens to every session and 869 once invoked, about $0.0005 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.
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