Creator · Yuan1z0825
Last updated · Sep 2, 2026
>-
Sandbox only
Creator · Yuan1z0825
Last updated · Sep 2, 2026
>-
Sandbox only
Creator · Yuan1z0825
Last updated · Sep 2, 2026
>-
Sandbox only
Creator · Yuan1z0825
Last updated · Sep 2, 2026
>-
Sandbox only
Install targets
Codex install prompt
Install the "nature-reviewer" agent skill from https://github.com/Yuan1z0825/nature-skills/tree/main/skills/nature-reviewer. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: >- After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"yuan1z0825-nature-reviewer","task":"Install nature-reviewer","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add Yuan1z0825/nature-skills --skill nature-reviewer
Maintenance
fresh
4d since push
Risk
Safe to try
The skill relies on subagent isolation for mutual blindness, which may not be fully achievable in all execution environments. The skill does acknowledge this and provides fallback instructions, but it remains a practical limitation.
GitHub quality
39K
93/100 Quality · 81/100 Trust
Coverage tags
Review notes
The skill relies on subagent isolation for mutual blindness, which may not be fully achievable in all execution environments. The skill does acknowledge this and provides fallback instructions, but it remains a practical limitation. · README/SKILL.md completeness: Public metadata needs stronger README/SKILL.md context
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
ExcellentHigh-confidence pick with strong adoption and healthy maintenance signals.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Safe to tryA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
39K GitHub stars
Repo activity
39K stars, 2.1K forks
Maintenance
4d since push
License
Apache-2.0
Install
npx skills add Yuan1z0825/nature-skills --skill nature-reviewer
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add Yuan1z0825/nature-skills --skill nature-reviewerDo not use when
Agent safety v2
Good audit and safety signals with no high-risk permission hints in public metadata.
Review the audit page, then allow agent install in a sandboxed workflow.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20nature-reviewer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20nature-reviewer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/yuan1z0825-nature-reviewer/install
Agent should check
Copy prompt
Task: Use nature-reviewer in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20nature-reviewer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/yuan1z0825-nature-reviewer/install
Install command: npx skills add Yuan1z0825/nature-skills --skill nature-reviewer
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/yuan1z0825-nature-reviewer/install
LLM text format
/api/skills/yuan1z0825-nature-reviewer/install?format=text
Find alternatives
/api/skills/search?q=nature-reviewer&limit=3
Agent prompt
Use nature-reviewer for this task. Review https://www.openagentskill.com/api/skills/yuan1z0825-nature-reviewer/install, then install with: npx skills add Yuan1z0825/nature-skills --skill nature-reviewerRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/yuan1z0825-nature-reviewer
LLM text
/api/registry/manifest/yuan1z0825-nature-reviewer?format=text
Install alias
/api/registry/install/yuan1z0825-nature-reviewer
Recommend
/api/registry/recommend?task=Use%20nature-reviewer%20in%20an%20agent%20workflow&limit=3
Agent fit
Local desktop
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Local desktop
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
PASS39K GitHub stars
Stars/forks activity
PASS39K stars, 2.1K forks; issue activity unavailable in current metadata
Recent maintenance
PASS4d since push
License clarity
PASSApache-2.0
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
High-confidence pick with strong adoption and healthy maintenance signals.
Workflow fit
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Workflow fit
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Alternative shortlist
Similar skills that may fit this task.
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--- name: nature-reviewer description: >- Simulate Nature-style or general pre-submission peer review from the referee perspective, not an author rebuttal. Use for reviewer reports, mock peer review, manuscript critique, novelty/significance/technical-soundness assessment, 审稿人视角评估, 模拟审稿, 预审, 投稿前自审, 审稿意见模拟, or 帮我审一下论文. Produce evidence-grounded Major Concerns, Minor Comments, and blocking flags. For multiple reviewers, keep every reviewer mutually blind in a separate context, freeze all reports before comparison, and create any synthesis only afterward as a separate editor/author-facing artifact. ---
# Nature Reviewer Assessment Skill
Use this skill to simulate a `Nature`-style reviewer assessment package from the referee side.
This skill is for reviewer-style manuscript evaluation, not for drafting the authors' response. If the user wants rebuttal writing, route to `nature-response`.
## Default stance
- Ground the review only in the local source basis plus manuscript facts supplied by the user. - Evaluate the manuscript against source-grounded axes: `originality`, `scientific importance`, `interdisciplinary readership`, `technical soundness`, and `readability for nonspecialists`. - Use the 12-axis technical concern taxonomy only as an internal coverage checklist; it supplements but never replaces the five source-grounded axes. - Return exactly `3 mutually blind reviewer reports + 1 post-review synthesis` unless the user explicitly asks for another structure. - Give every reviewer only the same immutable manuscript/source packet, the same journal criteria, and that reviewer's preassigned emphasis. Never provide another review, a shared concern ledger, a draft synthesis, or hints about what another reviewer noticed. - Run each reviewer in a genuinely separate context, subagent, process, or invocation. If the environment cannot isolate contexts, generate one reviewer report per invocation or explicitly state that mutual blindness cannot be guaranteed; never present shared-context drafting as independent peer review. - Define emphasis briefs before any report is generated. They are working lenses, not reviewer identities, specialties, institutions, or biographies. - Freeze each individual report before comparing them. Natural duplication or disagreement is valid evidence of independent review and must not be edited away to manufacture diversity. - Identify who would be interested in the results and why. - Identify technical failings that must be addressed before the authors' case is established. - Give every substantive concern a stable ID, a faithful `claim_pointer`, and a verifiable `evidence_pointer`; mark missing locations instead of inventing them. - Separate user-visible concerns into `Major Concerns` and `Minor Comments`. Mark a Major Concern `Blocking Yes` only when the current manuscript cannot establish its central case until that concern is resolved; Minor Comments are never blocking. - Do not impose a concern quota. If no grounded concern exists at a level, state that explicitly instead of inventing one. - Keep the critique intellectually sharp but professionally phrased; severity comes from impact on the manuscript's case, not from hostile wording. - Avoid em dashes, en dashes, and colons as routine prose punctuation throughout reviewer reports and synthesis. Prefer a new sentence, comma, semicolon, parentheses, or a short heading followed by a new line. Retain ordinary hyphens in standard compound terms and stable IDs such as `R1-M1`. Preserve punctuation in source-faithful titles, quotations, formulas, identifiers, URLs, times, and required machine-readable syntax when changing it would be inaccurate. - Distinguish clearly between what is supported, what is weak, and what is not assessable from the provided material. - When the manuscript has a clear technical domain, use claim-dependent domain gates as supporting checks, but keep the output inside the same 3-reviewer `nature-reviewer` structure. - Do not claim the editor's final decision or certainty about fit to `Nature`.
## Accepted inputs
The skill may receive:
- full manuscript draft - abstract, summary paragraph, or cover-summary style text - introduction, results, discussion, or methods excerpts - figure legends, selected figures, or result notes - author notes in Chinese or English describing the claimed contribution - pre-submission positioning notes
If the provided material is partial, perform a bounded review and mark the assessment boundary explicitly.
## Workflow
1. Identify the input scope and whether the job is a reviewer-style assessment rather than rebuttal drafting. 2. Build one immutable review packet containing only the supplied manuscript, verified source anchors, assessment boundary, and common journal criteria. Do not add analytical conclusions or suspected concerns to this packet. 3. Define the reviewer count and emphasis briefs before launching any reviewer. 4. Launch each reviewer in an isolated context. Pass only the immutable review packet, that reviewer's emphasis brief, the common report skeleton, and the same grounding rules. 5. Inside each isolated review, independently assess readiness and the source-grounded axes, then build that reviewer's own concern ledger using `references/technical-concern-taxonomy.md`. If relevant, load only the applicable section of `references/domain-specific-review-gates.md` inside that same isolated context. 6. Finalize and freeze every reviewer report. Do not show a completed or partial report to another reviewer, and do not redistribute concerns to control overlap. 7. Only after all reports are frozen, compare them in a separate synthesis pass. Reconcile independently created concerns to shared synthesis keys, and label consensus only when at least two reports independently raise the same underlying concern. 8. Generate `Cross-review synthesis (post-review; not shown to reviewers)` with consensus blocking concerns, other major concerns, the minor-revision checklist, and genuine differences in emphasis or judgment. 9. Run QA for reviewer isolation, severity calibration, blocking calibration, evidence anchoring, groundedness, coverage, role boundaries, and non-invention. Overlap is measured only after freezing and must never trigger retroactive rewriting of individual reports.
## Output format
Unless the user asks for another format, return:
```text Review setup - **Input scope** [value] - **Assessment boundary** [value] - **Shared manuscript claim summary** [value] - **Visible evidence base** [value] - **Missing materials affecting confidence** [value]
Reviewer 1 - **Overall assessment** [text] - **Who would be interested in the results, and why** [text] - **Major strengths** [text] - **Major Concerns** [items] - **Minor Comments** [items] - **Technical failings that need to be addressed before the case is established** [IDs or summary] - **Assessment against Nature-style criteria** [text] - **Recommendation posture** [text]
For each Major Concern - **Concern ID** R1-M1 - **Severity** Major - **Blocking** Yes / No - **Axis** [value] - **Claim pointer** [value] - **Evidence pointer** [value] - **Concern** [text] - **Why it matters** [text] - **Resolution test** [text]
For each Minor Comment - **Concern ID** R1-m1 - **Severity** Minor - **Axis** [value] - **Affected element** [value] - **Evidence pointer** [value] - **Issue** [text] - **Required correction** [text]
Reviewer 2 [Same structure]
Reviewer 3 [Same structure]
Cross-review synthesis (post-review; not shown to reviewers) - **Consensus strengths** [text] - **Consensus blocking concerns** [items] - **Other consensus major concerns** [items] - **Where emphasis differs across reviewers** [text] - **Minor revision checklist** [items] - **Broad-interest / significance readout** [text] - **Most important issues to resolve before a strong Nature-style case is established** [items]
Risk / unsupported claims - [specific unsupported or not-assessable items] ```
## Red lines
- Do not invent reviewer identities, specialty roles, or selection history. - Do not let one reviewer read, cite, anticipate, agree with, or respond to another review. - Do not build or distribute a shared concern ledger before individual reports are frozen. - Do not rewrite independent reports after comparison merely to reduce duplication or create artificial disagreement. - Do not call reports mutually blind when they were generated in a shared context without an explicit limitation notice. - Do not use dash punctuation or colons as habitual sentence connectors when clearer punctuation, headings, or sentence boundaries work. - Do not invent experiments, validations, controls, citations, figure details, line numbers, or prior-work distinctions not present in the input. - Do not silently turn reviewer assessment into author rebuttal drafting. - Do not present the review as an editorial decision letter. - Do not state that the manuscript belongs in `Nature` as a settled fact. - Do not omit technical failings when the provided evidence does not establish the authors' case. - Do not create Major or Minor concerns merely to fill a quota or make reviewer reports look balanced. - Do not downgrade a core evidence, validity, ethics, or integrity problem to Minor because it is easy to describe, and do not upgrade a local presentation issue merely to sound severe.
## Related files
| File | Open when | |---|---| | [references/source-basis.md](references/source-basis.md) | You need source provenance, local rule summaries, or source-vs-implementation boundaries | | [references/reviewer-workflow.md](references/reviewer-workflow.md) | You need the invocation order, fact-base extraction flow, or synthesis rules | | [references/review-axes.md](references/review-axes.md) | You need the evaluation axes or reviewer weighting logic | | [references/technical-concern-taxonomy.md](references/technical-concern-taxonomy.md) | You need the internal 12-axis coverage check, concern ledger, or claim/evidence-pointer rules | | [references/domain-specific-review-gates.md](references/domain-specific-review-gates.md) | The manuscript has clear chemistry, engineering, materials, atmospheric, climate-ecology, hydrology, or remote-sensing evidence chains | | [references/report-structure.md](references/report-structure.md) | You need the default output contract or section anatomy | | [references/role-boundaries.md](references/role-boundaries.md) | You need constraints on reviewer differences and editor-versus-reviewer boundaries | | [references/qa-checklist.md](references/qa-checklist.md) | You are finalizing an output and need groundedness / non-invention checks | | [../nature-shared/core/consistency-sweep.md](../nature-shared/core/consistency-sweep.md) | You are checking the manuscript against itself: headline counts that do not reconcile with the Methods, one metric at two precisions, a superlative contradicted by the paper's own table, overlapping error bars presented as an advantage, or internal summaries that disagree | | [references/editorial criteria and processes.md](<references/editorial criteria and processes.md>) | You need the primary local Nature source text |
## Source hierarchy
Use sources in this order:
1. `references/editorial criteria and processes.md` 2. manuscript facts supplied by the user 3. conservative local implementation rules documented in `references/source-basis.md` 4. domain-specific supporting gates in `references/domain-specific-review-gates.md`
If a user asks for policy-level certainty beyond this local source, state the limit instead of improvising broader journal policy.
Source provenance
Decision snapshot
38,695 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for nature-reviewer, ready for a manual X post.
A practical pick for a repeatable workflow: nature-reviewer: >- 38.7K stars https://www.openagentskill.com/skills/yuan1z0825-nature-reviewer?ref=x
Listing + install path for nature-reviewer: https://www.openagentskill.com/skills/yuan1z0825-nature-reviewer?ref=x Install: npx skills add Yuan1z0825/nature-skills --skill nature-reviewer
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
This Registry indexed listing is attributed to Yuan1z0825 but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
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Codex install prompt
Install the "nature-reviewer" agent skill from https://github.com/Yuan1z0825/nature-skills/tree/main/skills/nature-reviewer. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: >- After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"yuan1z0825-nature-reviewer","task":"Install nature-reviewer","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add Yuan1z0825/nature-skills --skill nature-reviewer
Maintenance
fresh
4d since push
Risk
Safe to try
The skill relies on subagent isolation for mutual blindness, which may not be fully achievable in all execution environments. The skill does acknowledge this and provides fallback instructions, but it remains a practical limitation.
GitHub quality
39K
93/100 Quality · 81/100 Trust
Coverage tags
Review notes
The skill relies on subagent isolation for mutual blindness, which may not be fully achievable in all execution environments. The skill does acknowledge this and provides fallback instructions, but it remains a practical limitation. · README/SKILL.md completeness: Public metadata needs stronger README/SKILL.md context
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
ExcellentHigh-confidence pick with strong adoption and healthy maintenance signals.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Safe to tryA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
39K GitHub stars
Repo activity
39K stars, 2.1K forks
Maintenance
4d since push
License
Apache-2.0
Install
npx skills add Yuan1z0825/nature-skills --skill nature-reviewer
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add Yuan1z0825/nature-skills --skill nature-reviewerDo not use when
Agent safety v2
Good audit and safety signals with no high-risk permission hints in public metadata.
Review the audit page, then allow agent install in a sandboxed workflow.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20nature-reviewer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20nature-reviewer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/yuan1z0825-nature-reviewer/install
Agent should check
Copy prompt
Task: Use nature-reviewer in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20nature-reviewer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/yuan1z0825-nature-reviewer/install
Install command: npx skills add Yuan1z0825/nature-skills --skill nature-reviewer
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/yuan1z0825-nature-reviewer/install
LLM text format
/api/skills/yuan1z0825-nature-reviewer/install?format=text
Find alternatives
/api/skills/search?q=nature-reviewer&limit=3
Agent prompt
Use nature-reviewer for this task. Review https://www.openagentskill.com/api/skills/yuan1z0825-nature-reviewer/install, then install with: npx skills add Yuan1z0825/nature-skills --skill nature-reviewerRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/yuan1z0825-nature-reviewer
LLM text
/api/registry/manifest/yuan1z0825-nature-reviewer?format=text
Install alias
/api/registry/install/yuan1z0825-nature-reviewer
Recommend
/api/registry/recommend?task=Use%20nature-reviewer%20in%20an%20agent%20workflow&limit=3
Agent fit
Local desktop
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Local desktop
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
PASS39K GitHub stars
Stars/forks activity
PASS39K stars, 2.1K forks; issue activity unavailable in current metadata
Recent maintenance
PASS4d since push
License clarity
PASSApache-2.0
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
High-confidence pick with strong adoption and healthy maintenance signals.
Workflow fit
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Workflow fit
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Alternative shortlist
Similar skills that may fit this task.
Run multimodal agents that operate desktop interfaces
Connect agents to hundreds of workflow automations
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Alternative firmware for ESP8266 and ESP32 based devices with easy configuration using webUI, OTA updates, automation using timers or rules, expandability and entirely local control over MQTT, HTTP, Serial or KNX. Full documentation at
--- name: nature-reviewer description: >- Simulate Nature-style or general pre-submission peer review from the referee perspective, not an author rebuttal. Use for reviewer reports, mock peer review, manuscript critique, novelty/significance/technical-soundness assessment, 审稿人视角评估, 模拟审稿, 预审, 投稿前自审, 审稿意见模拟, or 帮我审一下论文. Produce evidence-grounded Major Concerns, Minor Comments, and blocking flags. For multiple reviewers, keep every reviewer mutually blind in a separate context, freeze all reports before comparison, and create any synthesis only afterward as a separate editor/author-facing artifact. ---
# Nature Reviewer Assessment Skill
Use this skill to simulate a `Nature`-style reviewer assessment package from the referee side.
This skill is for reviewer-style manuscript evaluation, not for drafting the authors' response. If the user wants rebuttal writing, route to `nature-response`.
## Default stance
- Ground the review only in the local source basis plus manuscript facts supplied by the user. - Evaluate the manuscript against source-grounded axes: `originality`, `scientific importance`, `interdisciplinary readership`, `technical soundness`, and `readability for nonspecialists`. - Use the 12-axis technical concern taxonomy only as an internal coverage checklist; it supplements but never replaces the five source-grounded axes. - Return exactly `3 mutually blind reviewer reports + 1 post-review synthesis` unless the user explicitly asks for another structure. - Give every reviewer only the same immutable manuscript/source packet, the same journal criteria, and that reviewer's preassigned emphasis. Never provide another review, a shared concern ledger, a draft synthesis, or hints about what another reviewer noticed. - Run each reviewer in a genuinely separate context, subagent, process, or invocation. If the environment cannot isolate contexts, generate one reviewer report per invocation or explicitly state that mutual blindness cannot be guaranteed; never present shared-context drafting as independent peer review. - Define emphasis briefs before any report is generated. They are working lenses, not reviewer identities, specialties, institutions, or biographies. - Freeze each individual report before comparing them. Natural duplication or disagreement is valid evidence of independent review and must not be edited away to manufacture diversity. - Identify who would be interested in the results and why. - Identify technical failings that must be addressed before the authors' case is established. - Give every substantive concern a stable ID, a faithful `claim_pointer`, and a verifiable `evidence_pointer`; mark missing locations instead of inventing them. - Separate user-visible concerns into `Major Concerns` and `Minor Comments`. Mark a Major Concern `Blocking Yes` only when the current manuscript cannot establish its central case until that concern is resolved; Minor Comments are never blocking. - Do not impose a concern quota. If no grounded concern exists at a level, state that explicitly instead of inventing one. - Keep the critique intellectually sharp but professionally phrased; severity comes from impact on the manuscript's case, not from hostile wording. - Avoid em dashes, en dashes, and colons as routine prose punctuation throughout reviewer reports and synthesis. Prefer a new sentence, comma, semicolon, parentheses, or a short heading followed by a new line. Retain ordinary hyphens in standard compound terms and stable IDs such as `R1-M1`. Preserve punctuation in source-faithful titles, quotations, formulas, identifiers, URLs, times, and required machine-readable syntax when changing it would be inaccurate. - Distinguish clearly between what is supported, what is weak, and what is not assessable from the provided material. - When the manuscript has a clear technical domain, use claim-dependent domain gates as supporting checks, but keep the output inside the same 3-reviewer `nature-reviewer` structure. - Do not claim the editor's final decision or certainty about fit to `Nature`.
## Accepted inputs
The skill may receive:
- full manuscript draft - abstract, summary paragraph, or cover-summary style text - introduction, results, discussion, or methods excerpts - figure legends, selected figures, or result notes - author notes in Chinese or English describing the claimed contribution - pre-submission positioning notes
If the provided material is partial, perform a bounded review and mark the assessment boundary explicitly.
## Workflow
1. Identify the input scope and whether the job is a reviewer-style assessment rather than rebuttal drafting. 2. Build one immutable review packet containing only the supplied manuscript, verified source anchors, assessment boundary, and common journal criteria. Do not add analytical conclusions or suspected concerns to this packet. 3. Define the reviewer count and emphasis briefs before launching any reviewer. 4. Launch each reviewer in an isolated context. Pass only the immutable review packet, that reviewer's emphasis brief, the common report skeleton, and the same grounding rules. 5. Inside each isolated review, independently assess readiness and the source-grounded axes, then build that reviewer's own concern ledger using `references/technical-concern-taxonomy.md`. If relevant, load only the applicable section of `references/domain-specific-review-gates.md` inside that same isolated context. 6. Finalize and freeze every reviewer report. Do not show a completed or partial report to another reviewer, and do not redistribute concerns to control overlap. 7. Only after all reports are frozen, compare them in a separate synthesis pass. Reconcile independently created concerns to shared synthesis keys, and label consensus only when at least two reports independently raise the same underlying concern. 8. Generate `Cross-review synthesis (post-review; not shown to reviewers)` with consensus blocking concerns, other major concerns, the minor-revision checklist, and genuine differences in emphasis or judgment. 9. Run QA for reviewer isolation, severity calibration, blocking calibration, evidence anchoring, groundedness, coverage, role boundaries, and non-invention. Overlap is measured only after freezing and must never trigger retroactive rewriting of individual reports.
## Output format
Unless the user asks for another format, return:
```text Review setup - **Input scope** [value] - **Assessment boundary** [value] - **Shared manuscript claim summary** [value] - **Visible evidence base** [value] - **Missing materials affecting confidence** [value]
Reviewer 1 - **Overall assessment** [text] - **Who would be interested in the results, and why** [text] - **Major strengths** [text] - **Major Concerns** [items] - **Minor Comments** [items] - **Technical failings that need to be addressed before the case is established** [IDs or summary] - **Assessment against Nature-style criteria** [text] - **Recommendation posture** [text]
For each Major Concern - **Concern ID** R1-M1 - **Severity** Major - **Blocking** Yes / No - **Axis** [value] - **Claim pointer** [value] - **Evidence pointer** [value] - **Concern** [text] - **Why it matters** [text] - **Resolution test** [text]
For each Minor Comment - **Concern ID** R1-m1 - **Severity** Minor - **Axis** [value] - **Affected element** [value] - **Evidence pointer** [value] - **Issue** [text] - **Required correction** [text]
Reviewer 2 [Same structure]
Reviewer 3 [Same structure]
Cross-review synthesis (post-review; not shown to reviewers) - **Consensus strengths** [text] - **Consensus blocking concerns** [items] - **Other consensus major concerns** [items] - **Where emphasis differs across reviewers** [text] - **Minor revision checklist** [items] - **Broad-interest / significance readout** [text] - **Most important issues to resolve before a strong Nature-style case is established** [items]
Risk / unsupported claims - [specific unsupported or not-assessable items] ```
## Red lines
- Do not invent reviewer identities, specialty roles, or selection history. - Do not let one reviewer read, cite, anticipate, agree with, or respond to another review. - Do not build or distribute a shared concern ledger before individual reports are frozen. - Do not rewrite independent reports after comparison merely to reduce duplication or create artificial disagreement. - Do not call reports mutually blind when they were generated in a shared context without an explicit limitation notice. - Do not use dash punctuation or colons as habitual sentence connectors when clearer punctuation, headings, or sentence boundaries work. - Do not invent experiments, validations, controls, citations, figure details, line numbers, or prior-work distinctions not present in the input. - Do not silently turn reviewer assessment into author rebuttal drafting. - Do not present the review as an editorial decision letter. - Do not state that the manuscript belongs in `Nature` as a settled fact. - Do not omit technical failings when the provided evidence does not establish the authors' case. - Do not create Major or Minor concerns merely to fill a quota or make reviewer reports look balanced. - Do not downgrade a core evidence, validity, ethics, or integrity problem to Minor because it is easy to describe, and do not upgrade a local presentation issue merely to sound severe.
## Related files
| File | Open when | |---|---| | [references/source-basis.md](references/source-basis.md) | You need source provenance, local rule summaries, or source-vs-implementation boundaries | | [references/reviewer-workflow.md](references/reviewer-workflow.md) | You need the invocation order, fact-base extraction flow, or synthesis rules | | [references/review-axes.md](references/review-axes.md) | You need the evaluation axes or reviewer weighting logic | | [references/technical-concern-taxonomy.md](references/technical-concern-taxonomy.md) | You need the internal 12-axis coverage check, concern ledger, or claim/evidence-pointer rules | | [references/domain-specific-review-gates.md](references/domain-specific-review-gates.md) | The manuscript has clear chemistry, engineering, materials, atmospheric, climate-ecology, hydrology, or remote-sensing evidence chains | | [references/report-structure.md](references/report-structure.md) | You need the default output contract or section anatomy | | [references/role-boundaries.md](references/role-boundaries.md) | You need constraints on reviewer differences and editor-versus-reviewer boundaries | | [references/qa-checklist.md](references/qa-checklist.md) | You are finalizing an output and need groundedness / non-invention checks | | [../nature-shared/core/consistency-sweep.md](../nature-shared/core/consistency-sweep.md) | You are checking the manuscript against itself: headline counts that do not reconcile with the Methods, one metric at two precisions, a superlative contradicted by the paper's own table, overlapping error bars presented as an advantage, or internal summaries that disagree | | [references/editorial criteria and processes.md](<references/editorial criteria and processes.md>) | You need the primary local Nature source text |
## Source hierarchy
Use sources in this order:
1. `references/editorial criteria and processes.md` 2. manuscript facts supplied by the user 3. conservative local implementation rules documented in `references/source-basis.md` 4. domain-specific supporting gates in `references/domain-specific-review-gates.md`
If a user asks for policy-level certainty beyond this local source, state the limit instead of improvising broader journal policy.
Source provenance
Decision snapshot
38,695 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for nature-reviewer, ready for a manual X post.
A practical pick for a repeatable workflow: nature-reviewer: >- 38.7K stars https://www.openagentskill.com/skills/yuan1z0825-nature-reviewer?ref=x
Listing + install path for nature-reviewer: https://www.openagentskill.com/skills/yuan1z0825-nature-reviewer?ref=x Install: npx skills add Yuan1z0825/nature-skills --skill nature-reviewer
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
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@yuan1z0825
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UI-TARS Desktop
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24.7K StarsInstall targets
Codex install prompt
Install the "nature-reviewer" agent skill from https://github.com/Yuan1z0825/nature-skills/tree/main/skills/nature-reviewer. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: >- After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"yuan1z0825-nature-reviewer","task":"Install nature-reviewer","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add Yuan1z0825/nature-skills --skill nature-reviewer
Maintenance
fresh
4d since push
Risk
Safe to try
The skill relies on subagent isolation for mutual blindness, which may not be fully achievable in all execution environments. The skill does acknowledge this and provides fallback instructions, but it remains a practical limitation.
GitHub quality
39K
93/100 Quality · 81/100 Trust
Coverage tags
Review notes
The skill relies on subagent isolation for mutual blindness, which may not be fully achievable in all execution environments. The skill does acknowledge this and provides fallback instructions, but it remains a practical limitation. · README/SKILL.md completeness: Public metadata needs stronger README/SKILL.md context
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
ExcellentHigh-confidence pick with strong adoption and healthy maintenance signals.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Safe to tryA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
39K GitHub stars
Repo activity
39K stars, 2.1K forks
Maintenance
4d since push
License
Apache-2.0
Install
npx skills add Yuan1z0825/nature-skills --skill nature-reviewer
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add Yuan1z0825/nature-skills --skill nature-reviewerDo not use when
Agent safety v2
Good audit and safety signals with no high-risk permission hints in public metadata.
Review the audit page, then allow agent install in a sandboxed workflow.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20nature-reviewer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20nature-reviewer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/yuan1z0825-nature-reviewer/install
Agent should check
Copy prompt
Task: Use nature-reviewer in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20nature-reviewer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/yuan1z0825-nature-reviewer/install
Install command: npx skills add Yuan1z0825/nature-skills --skill nature-reviewer
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/yuan1z0825-nature-reviewer/install
LLM text format
/api/skills/yuan1z0825-nature-reviewer/install?format=text
Find alternatives
/api/skills/search?q=nature-reviewer&limit=3
Agent prompt
Use nature-reviewer for this task. Review https://www.openagentskill.com/api/skills/yuan1z0825-nature-reviewer/install, then install with: npx skills add Yuan1z0825/nature-skills --skill nature-reviewerRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/yuan1z0825-nature-reviewer
LLM text
/api/registry/manifest/yuan1z0825-nature-reviewer?format=text
Install alias
/api/registry/install/yuan1z0825-nature-reviewer
Recommend
/api/registry/recommend?task=Use%20nature-reviewer%20in%20an%20agent%20workflow&limit=3
Agent fit
Local desktop
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Local desktop
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
PASS39K GitHub stars
Stars/forks activity
PASS39K stars, 2.1K forks; issue activity unavailable in current metadata
Recent maintenance
PASS4d since push
License clarity
PASSApache-2.0
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
High-confidence pick with strong adoption and healthy maintenance signals.
Workflow fit
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Workflow fit
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Alternative shortlist
Similar skills that may fit this task.
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--- name: nature-reviewer description: >- Simulate Nature-style or general pre-submission peer review from the referee perspective, not an author rebuttal. Use for reviewer reports, mock peer review, manuscript critique, novelty/significance/technical-soundness assessment, 审稿人视角评估, 模拟审稿, 预审, 投稿前自审, 审稿意见模拟, or 帮我审一下论文. Produce evidence-grounded Major Concerns, Minor Comments, and blocking flags. For multiple reviewers, keep every reviewer mutually blind in a separate context, freeze all reports before comparison, and create any synthesis only afterward as a separate editor/author-facing artifact. ---
# Nature Reviewer Assessment Skill
Use this skill to simulate a `Nature`-style reviewer assessment package from the referee side.
This skill is for reviewer-style manuscript evaluation, not for drafting the authors' response. If the user wants rebuttal writing, route to `nature-response`.
## Default stance
- Ground the review only in the local source basis plus manuscript facts supplied by the user. - Evaluate the manuscript against source-grounded axes: `originality`, `scientific importance`, `interdisciplinary readership`, `technical soundness`, and `readability for nonspecialists`. - Use the 12-axis technical concern taxonomy only as an internal coverage checklist; it supplements but never replaces the five source-grounded axes. - Return exactly `3 mutually blind reviewer reports + 1 post-review synthesis` unless the user explicitly asks for another structure. - Give every reviewer only the same immutable manuscript/source packet, the same journal criteria, and that reviewer's preassigned emphasis. Never provide another review, a shared concern ledger, a draft synthesis, or hints about what another reviewer noticed. - Run each reviewer in a genuinely separate context, subagent, process, or invocation. If the environment cannot isolate contexts, generate one reviewer report per invocation or explicitly state that mutual blindness cannot be guaranteed; never present shared-context drafting as independent peer review. - Define emphasis briefs before any report is generated. They are working lenses, not reviewer identities, specialties, institutions, or biographies. - Freeze each individual report before comparing them. Natural duplication or disagreement is valid evidence of independent review and must not be edited away to manufacture diversity. - Identify who would be interested in the results and why. - Identify technical failings that must be addressed before the authors' case is established. - Give every substantive concern a stable ID, a faithful `claim_pointer`, and a verifiable `evidence_pointer`; mark missing locations instead of inventing them. - Separate user-visible concerns into `Major Concerns` and `Minor Comments`. Mark a Major Concern `Blocking Yes` only when the current manuscript cannot establish its central case until that concern is resolved; Minor Comments are never blocking. - Do not impose a concern quota. If no grounded concern exists at a level, state that explicitly instead of inventing one. - Keep the critique intellectually sharp but professionally phrased; severity comes from impact on the manuscript's case, not from hostile wording. - Avoid em dashes, en dashes, and colons as routine prose punctuation throughout reviewer reports and synthesis. Prefer a new sentence, comma, semicolon, parentheses, or a short heading followed by a new line. Retain ordinary hyphens in standard compound terms and stable IDs such as `R1-M1`. Preserve punctuation in source-faithful titles, quotations, formulas, identifiers, URLs, times, and required machine-readable syntax when changing it would be inaccurate. - Distinguish clearly between what is supported, what is weak, and what is not assessable from the provided material. - When the manuscript has a clear technical domain, use claim-dependent domain gates as supporting checks, but keep the output inside the same 3-reviewer `nature-reviewer` structure. - Do not claim the editor's final decision or certainty about fit to `Nature`.
## Accepted inputs
The skill may receive:
- full manuscript draft - abstract, summary paragraph, or cover-summary style text - introduction, results, discussion, or methods excerpts - figure legends, selected figures, or result notes - author notes in Chinese or English describing the claimed contribution - pre-submission positioning notes
If the provided material is partial, perform a bounded review and mark the assessment boundary explicitly.
## Workflow
1. Identify the input scope and whether the job is a reviewer-style assessment rather than rebuttal drafting. 2. Build one immutable review packet containing only the supplied manuscript, verified source anchors, assessment boundary, and common journal criteria. Do not add analytical conclusions or suspected concerns to this packet. 3. Define the reviewer count and emphasis briefs before launching any reviewer. 4. Launch each reviewer in an isolated context. Pass only the immutable review packet, that reviewer's emphasis brief, the common report skeleton, and the same grounding rules. 5. Inside each isolated review, independently assess readiness and the source-grounded axes, then build that reviewer's own concern ledger using `references/technical-concern-taxonomy.md`. If relevant, load only the applicable section of `references/domain-specific-review-gates.md` inside that same isolated context. 6. Finalize and freeze every reviewer report. Do not show a completed or partial report to another reviewer, and do not redistribute concerns to control overlap. 7. Only after all reports are frozen, compare them in a separate synthesis pass. Reconcile independently created concerns to shared synthesis keys, and label consensus only when at least two reports independently raise the same underlying concern. 8. Generate `Cross-review synthesis (post-review; not shown to reviewers)` with consensus blocking concerns, other major concerns, the minor-revision checklist, and genuine differences in emphasis or judgment. 9. Run QA for reviewer isolation, severity calibration, blocking calibration, evidence anchoring, groundedness, coverage, role boundaries, and non-invention. Overlap is measured only after freezing and must never trigger retroactive rewriting of individual reports.
## Output format
Unless the user asks for another format, return:
```text Review setup - **Input scope** [value] - **Assessment boundary** [value] - **Shared manuscript claim summary** [value] - **Visible evidence base** [value] - **Missing materials affecting confidence** [value]
Reviewer 1 - **Overall assessment** [text] - **Who would be interested in the results, and why** [text] - **Major strengths** [text] - **Major Concerns** [items] - **Minor Comments** [items] - **Technical failings that need to be addressed before the case is established** [IDs or summary] - **Assessment against Nature-style criteria** [text] - **Recommendation posture** [text]
For each Major Concern - **Concern ID** R1-M1 - **Severity** Major - **Blocking** Yes / No - **Axis** [value] - **Claim pointer** [value] - **Evidence pointer** [value] - **Concern** [text] - **Why it matters** [text] - **Resolution test** [text]
For each Minor Comment - **Concern ID** R1-m1 - **Severity** Minor - **Axis** [value] - **Affected element** [value] - **Evidence pointer** [value] - **Issue** [text] - **Required correction** [text]
Reviewer 2 [Same structure]
Reviewer 3 [Same structure]
Cross-review synthesis (post-review; not shown to reviewers) - **Consensus strengths** [text] - **Consensus blocking concerns** [items] - **Other consensus major concerns** [items] - **Where emphasis differs across reviewers** [text] - **Minor revision checklist** [items] - **Broad-interest / significance readout** [text] - **Most important issues to resolve before a strong Nature-style case is established** [items]
Risk / unsupported claims - [specific unsupported or not-assessable items] ```
## Red lines
- Do not invent reviewer identities, specialty roles, or selection history. - Do not let one reviewer read, cite, anticipate, agree with, or respond to another review. - Do not build or distribute a shared concern ledger before individual reports are frozen. - Do not rewrite independent reports after comparison merely to reduce duplication or create artificial disagreement. - Do not call reports mutually blind when they were generated in a shared context without an explicit limitation notice. - Do not use dash punctuation or colons as habitual sentence connectors when clearer punctuation, headings, or sentence boundaries work. - Do not invent experiments, validations, controls, citations, figure details, line numbers, or prior-work distinctions not present in the input. - Do not silently turn reviewer assessment into author rebuttal drafting. - Do not present the review as an editorial decision letter. - Do not state that the manuscript belongs in `Nature` as a settled fact. - Do not omit technical failings when the provided evidence does not establish the authors' case. - Do not create Major or Minor concerns merely to fill a quota or make reviewer reports look balanced. - Do not downgrade a core evidence, validity, ethics, or integrity problem to Minor because it is easy to describe, and do not upgrade a local presentation issue merely to sound severe.
## Related files
| File | Open when | |---|---| | [references/source-basis.md](references/source-basis.md) | You need source provenance, local rule summaries, or source-vs-implementation boundaries | | [references/reviewer-workflow.md](references/reviewer-workflow.md) | You need the invocation order, fact-base extraction flow, or synthesis rules | | [references/review-axes.md](references/review-axes.md) | You need the evaluation axes or reviewer weighting logic | | [references/technical-concern-taxonomy.md](references/technical-concern-taxonomy.md) | You need the internal 12-axis coverage check, concern ledger, or claim/evidence-pointer rules | | [references/domain-specific-review-gates.md](references/domain-specific-review-gates.md) | The manuscript has clear chemistry, engineering, materials, atmospheric, climate-ecology, hydrology, or remote-sensing evidence chains | | [references/report-structure.md](references/report-structure.md) | You need the default output contract or section anatomy | | [references/role-boundaries.md](references/role-boundaries.md) | You need constraints on reviewer differences and editor-versus-reviewer boundaries | | [references/qa-checklist.md](references/qa-checklist.md) | You are finalizing an output and need groundedness / non-invention checks | | [../nature-shared/core/consistency-sweep.md](../nature-shared/core/consistency-sweep.md) | You are checking the manuscript against itself: headline counts that do not reconcile with the Methods, one metric at two precisions, a superlative contradicted by the paper's own table, overlapping error bars presented as an advantage, or internal summaries that disagree | | [references/editorial criteria and processes.md](<references/editorial criteria and processes.md>) | You need the primary local Nature source text |
## Source hierarchy
Use sources in this order:
1. `references/editorial criteria and processes.md` 2. manuscript facts supplied by the user 3. conservative local implementation rules documented in `references/source-basis.md` 4. domain-specific supporting gates in `references/domain-specific-review-gates.md`
If a user asks for policy-level certainty beyond this local source, state the limit instead of improvising broader journal policy.
Source provenance
Decision snapshot
38,695 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for nature-reviewer, ready for a manual X post.
A practical pick for a repeatable workflow: nature-reviewer: >- 38.7K stars https://www.openagentskill.com/skills/yuan1z0825-nature-reviewer?ref=x
Listing + install path for nature-reviewer: https://www.openagentskill.com/skills/yuan1z0825-nature-reviewer?ref=x Install: npx skills add Yuan1z0825/nature-skills --skill nature-reviewer
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@yuan1z0825
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Codex install prompt
Install the "nature-reviewer" agent skill from https://github.com/Yuan1z0825/nature-skills/tree/main/skills/nature-reviewer. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: >- After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"yuan1z0825-nature-reviewer","task":"Install nature-reviewer","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add Yuan1z0825/nature-skills --skill nature-reviewer
Maintenance
fresh
4d since push
Risk
Safe to try
The skill relies on subagent isolation for mutual blindness, which may not be fully achievable in all execution environments. The skill does acknowledge this and provides fallback instructions, but it remains a practical limitation.
GitHub quality
39K
93/100 Quality · 81/100 Trust
Coverage tags
Review notes
The skill relies on subagent isolation for mutual blindness, which may not be fully achievable in all execution environments. The skill does acknowledge this and provides fallback instructions, but it remains a practical limitation. · README/SKILL.md completeness: Public metadata needs stronger README/SKILL.md context
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
ExcellentHigh-confidence pick with strong adoption and healthy maintenance signals.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Safe to tryA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
39K GitHub stars
Repo activity
39K stars, 2.1K forks
Maintenance
4d since push
License
Apache-2.0
Install
npx skills add Yuan1z0825/nature-skills --skill nature-reviewer
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add Yuan1z0825/nature-skills --skill nature-reviewerDo not use when
Agent safety v2
Good audit and safety signals with no high-risk permission hints in public metadata.
Review the audit page, then allow agent install in a sandboxed workflow.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20nature-reviewer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20nature-reviewer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/yuan1z0825-nature-reviewer/install
Agent should check
Copy prompt
Task: Use nature-reviewer in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20nature-reviewer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/yuan1z0825-nature-reviewer/install
Install command: npx skills add Yuan1z0825/nature-skills --skill nature-reviewer
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/yuan1z0825-nature-reviewer/install
LLM text format
/api/skills/yuan1z0825-nature-reviewer/install?format=text
Find alternatives
/api/skills/search?q=nature-reviewer&limit=3
Agent prompt
Use nature-reviewer for this task. Review https://www.openagentskill.com/api/skills/yuan1z0825-nature-reviewer/install, then install with: npx skills add Yuan1z0825/nature-skills --skill nature-reviewerRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/yuan1z0825-nature-reviewer
LLM text
/api/registry/manifest/yuan1z0825-nature-reviewer?format=text
Install alias
/api/registry/install/yuan1z0825-nature-reviewer
Recommend
/api/registry/recommend?task=Use%20nature-reviewer%20in%20an%20agent%20workflow&limit=3
Agent fit
Local desktop
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Local desktop
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
PASS39K GitHub stars
Stars/forks activity
PASS39K stars, 2.1K forks; issue activity unavailable in current metadata
Recent maintenance
PASS4d since push
License clarity
PASSApache-2.0
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
High-confidence pick with strong adoption and healthy maintenance signals.
Workflow fit
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Workflow fit
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Alternative shortlist
Similar skills that may fit this task.
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--- name: nature-reviewer description: >- Simulate Nature-style or general pre-submission peer review from the referee perspective, not an author rebuttal. Use for reviewer reports, mock peer review, manuscript critique, novelty/significance/technical-soundness assessment, 审稿人视角评估, 模拟审稿, 预审, 投稿前自审, 审稿意见模拟, or 帮我审一下论文. Produce evidence-grounded Major Concerns, Minor Comments, and blocking flags. For multiple reviewers, keep every reviewer mutually blind in a separate context, freeze all reports before comparison, and create any synthesis only afterward as a separate editor/author-facing artifact. ---
# Nature Reviewer Assessment Skill
Use this skill to simulate a `Nature`-style reviewer assessment package from the referee side.
This skill is for reviewer-style manuscript evaluation, not for drafting the authors' response. If the user wants rebuttal writing, route to `nature-response`.
## Default stance
- Ground the review only in the local source basis plus manuscript facts supplied by the user. - Evaluate the manuscript against source-grounded axes: `originality`, `scientific importance`, `interdisciplinary readership`, `technical soundness`, and `readability for nonspecialists`. - Use the 12-axis technical concern taxonomy only as an internal coverage checklist; it supplements but never replaces the five source-grounded axes. - Return exactly `3 mutually blind reviewer reports + 1 post-review synthesis` unless the user explicitly asks for another structure. - Give every reviewer only the same immutable manuscript/source packet, the same journal criteria, and that reviewer's preassigned emphasis. Never provide another review, a shared concern ledger, a draft synthesis, or hints about what another reviewer noticed. - Run each reviewer in a genuinely separate context, subagent, process, or invocation. If the environment cannot isolate contexts, generate one reviewer report per invocation or explicitly state that mutual blindness cannot be guaranteed; never present shared-context drafting as independent peer review. - Define emphasis briefs before any report is generated. They are working lenses, not reviewer identities, specialties, institutions, or biographies. - Freeze each individual report before comparing them. Natural duplication or disagreement is valid evidence of independent review and must not be edited away to manufacture diversity. - Identify who would be interested in the results and why. - Identify technical failings that must be addressed before the authors' case is established. - Give every substantive concern a stable ID, a faithful `claim_pointer`, and a verifiable `evidence_pointer`; mark missing locations instead of inventing them. - Separate user-visible concerns into `Major Concerns` and `Minor Comments`. Mark a Major Concern `Blocking Yes` only when the current manuscript cannot establish its central case until that concern is resolved; Minor Comments are never blocking. - Do not impose a concern quota. If no grounded concern exists at a level, state that explicitly instead of inventing one. - Keep the critique intellectually sharp but professionally phrased; severity comes from impact on the manuscript's case, not from hostile wording. - Avoid em dashes, en dashes, and colons as routine prose punctuation throughout reviewer reports and synthesis. Prefer a new sentence, comma, semicolon, parentheses, or a short heading followed by a new line. Retain ordinary hyphens in standard compound terms and stable IDs such as `R1-M1`. Preserve punctuation in source-faithful titles, quotations, formulas, identifiers, URLs, times, and required machine-readable syntax when changing it would be inaccurate. - Distinguish clearly between what is supported, what is weak, and what is not assessable from the provided material. - When the manuscript has a clear technical domain, use claim-dependent domain gates as supporting checks, but keep the output inside the same 3-reviewer `nature-reviewer` structure. - Do not claim the editor's final decision or certainty about fit to `Nature`.
## Accepted inputs
The skill may receive:
- full manuscript draft - abstract, summary paragraph, or cover-summary style text - introduction, results, discussion, or methods excerpts - figure legends, selected figures, or result notes - author notes in Chinese or English describing the claimed contribution - pre-submission positioning notes
If the provided material is partial, perform a bounded review and mark the assessment boundary explicitly.
## Workflow
1. Identify the input scope and whether the job is a reviewer-style assessment rather than rebuttal drafting. 2. Build one immutable review packet containing only the supplied manuscript, verified source anchors, assessment boundary, and common journal criteria. Do not add analytical conclusions or suspected concerns to this packet. 3. Define the reviewer count and emphasis briefs before launching any reviewer. 4. Launch each reviewer in an isolated context. Pass only the immutable review packet, that reviewer's emphasis brief, the common report skeleton, and the same grounding rules. 5. Inside each isolated review, independently assess readiness and the source-grounded axes, then build that reviewer's own concern ledger using `references/technical-concern-taxonomy.md`. If relevant, load only the applicable section of `references/domain-specific-review-gates.md` inside that same isolated context. 6. Finalize and freeze every reviewer report. Do not show a completed or partial report to another reviewer, and do not redistribute concerns to control overlap. 7. Only after all reports are frozen, compare them in a separate synthesis pass. Reconcile independently created concerns to shared synthesis keys, and label consensus only when at least two reports independently raise the same underlying concern. 8. Generate `Cross-review synthesis (post-review; not shown to reviewers)` with consensus blocking concerns, other major concerns, the minor-revision checklist, and genuine differences in emphasis or judgment. 9. Run QA for reviewer isolation, severity calibration, blocking calibration, evidence anchoring, groundedness, coverage, role boundaries, and non-invention. Overlap is measured only after freezing and must never trigger retroactive rewriting of individual reports.
## Output format
Unless the user asks for another format, return:
```text Review setup - **Input scope** [value] - **Assessment boundary** [value] - **Shared manuscript claim summary** [value] - **Visible evidence base** [value] - **Missing materials affecting confidence** [value]
Reviewer 1 - **Overall assessment** [text] - **Who would be interested in the results, and why** [text] - **Major strengths** [text] - **Major Concerns** [items] - **Minor Comments** [items] - **Technical failings that need to be addressed before the case is established** [IDs or summary] - **Assessment against Nature-style criteria** [text] - **Recommendation posture** [text]
For each Major Concern - **Concern ID** R1-M1 - **Severity** Major - **Blocking** Yes / No - **Axis** [value] - **Claim pointer** [value] - **Evidence pointer** [value] - **Concern** [text] - **Why it matters** [text] - **Resolution test** [text]
For each Minor Comment - **Concern ID** R1-m1 - **Severity** Minor - **Axis** [value] - **Affected element** [value] - **Evidence pointer** [value] - **Issue** [text] - **Required correction** [text]
Reviewer 2 [Same structure]
Reviewer 3 [Same structure]
Cross-review synthesis (post-review; not shown to reviewers) - **Consensus strengths** [text] - **Consensus blocking concerns** [items] - **Other consensus major concerns** [items] - **Where emphasis differs across reviewers** [text] - **Minor revision checklist** [items] - **Broad-interest / significance readout** [text] - **Most important issues to resolve before a strong Nature-style case is established** [items]
Risk / unsupported claims - [specific unsupported or not-assessable items] ```
## Red lines
- Do not invent reviewer identities, specialty roles, or selection history. - Do not let one reviewer read, cite, anticipate, agree with, or respond to another review. - Do not build or distribute a shared concern ledger before individual reports are frozen. - Do not rewrite independent reports after comparison merely to reduce duplication or create artificial disagreement. - Do not call reports mutually blind when they were generated in a shared context without an explicit limitation notice. - Do not use dash punctuation or colons as habitual sentence connectors when clearer punctuation, headings, or sentence boundaries work. - Do not invent experiments, validations, controls, citations, figure details, line numbers, or prior-work distinctions not present in the input. - Do not silently turn reviewer assessment into author rebuttal drafting. - Do not present the review as an editorial decision letter. - Do not state that the manuscript belongs in `Nature` as a settled fact. - Do not omit technical failings when the provided evidence does not establish the authors' case. - Do not create Major or Minor concerns merely to fill a quota or make reviewer reports look balanced. - Do not downgrade a core evidence, validity, ethics, or integrity problem to Minor because it is easy to describe, and do not upgrade a local presentation issue merely to sound severe.
## Related files
| File | Open when | |---|---| | [references/source-basis.md](references/source-basis.md) | You need source provenance, local rule summaries, or source-vs-implementation boundaries | | [references/reviewer-workflow.md](references/reviewer-workflow.md) | You need the invocation order, fact-base extraction flow, or synthesis rules | | [references/review-axes.md](references/review-axes.md) | You need the evaluation axes or reviewer weighting logic | | [references/technical-concern-taxonomy.md](references/technical-concern-taxonomy.md) | You need the internal 12-axis coverage check, concern ledger, or claim/evidence-pointer rules | | [references/domain-specific-review-gates.md](references/domain-specific-review-gates.md) | The manuscript has clear chemistry, engineering, materials, atmospheric, climate-ecology, hydrology, or remote-sensing evidence chains | | [references/report-structure.md](references/report-structure.md) | You need the default output contract or section anatomy | | [references/role-boundaries.md](references/role-boundaries.md) | You need constraints on reviewer differences and editor-versus-reviewer boundaries | | [references/qa-checklist.md](references/qa-checklist.md) | You are finalizing an output and need groundedness / non-invention checks | | [../nature-shared/core/consistency-sweep.md](../nature-shared/core/consistency-sweep.md) | You are checking the manuscript against itself: headline counts that do not reconcile with the Methods, one metric at two precisions, a superlative contradicted by the paper's own table, overlapping error bars presented as an advantage, or internal summaries that disagree | | [references/editorial criteria and processes.md](<references/editorial criteria and processes.md>) | You need the primary local Nature source text |
## Source hierarchy
Use sources in this order:
1. `references/editorial criteria and processes.md` 2. manuscript facts supplied by the user 3. conservative local implementation rules documented in `references/source-basis.md` 4. domain-specific supporting gates in `references/domain-specific-review-gates.md`
If a user asks for policy-level certainty beyond this local source, state the limit instead of improvising broader journal policy.
Source provenance
Decision snapshot
38,695 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for nature-reviewer, ready for a manual X post.
A practical pick for a repeatable workflow: nature-reviewer: >- 38.7K stars https://www.openagentskill.com/skills/yuan1z0825-nature-reviewer?ref=x
Listing + install path for nature-reviewer: https://www.openagentskill.com/skills/yuan1z0825-nature-reviewer?ref=x Install: npx skills add Yuan1z0825/nature-skills --skill nature-reviewer
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
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[](https://www.openagentskill.com/skills/yuan1z0825-nature-reviewer?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/yuan1z0825-nature-reviewer?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
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[](https://www.openagentskill.com/skills/yuan1z0825-nature-reviewer?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)Yuan1z0825
@yuan1z0825
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filesystem or document access
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Thin public metadata
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filesystem or document access
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Docs
Thin public metadata
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Install readiness
Permission surface
filesystem or document access
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Thin public metadata
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Permission surface
filesystem or document access
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Thin public metadata
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Install readiness