academic-integrity-rewrite

REVIEW · 60
Registry indexed

Revise Chinese or English academic writing for lower unnecessary textual overlap while preserving meaning, evidence, numbers, equations, terminology, and citations. Use for 学术论文降重、查重后修改、重复段落重写、paraphrasing, similarity-report remediation, abstracts, literature reviews, methods, re

Verified installs0
Stars82
Version1.0.0
Quality66/100 · Promising
Trust60/100 · Sandbox only
Audit76/100 · Needs review

Supply asset profile

Research and knowledge work

Deep research, source comparison, literature review, RAG, knowledge search, and reports.

Browse track

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 lin1111-1/academic-integrity-rewrite --skill academic-integrity-rewrite

Maintenance

fresh

Pushed today

Risk

Needs review

The audit script's measurement regex may miss some uncommon unit notations (e.g., scientific notation, complex compound units), but this is explicitly acknowledged in the skill and manual review is recommended.

GitHub quality

82

66/100 Quality · 68/100 Trust

Coverage tags

ResearchResearch agentsagent-skill

Review notes

The audit script's measurement regex may miss some uncommon unit notations (e.g., scientific notation, complex compound units), but this is explicitly acknowledged in the skill and manual review is recommended. · No explicit handling for non-UTF8 encodings in plain text files, though most modern editors default to UTF-8.

Agent adoption scorecard

Trust, audit, and install readiness at a glance

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

Promising
66

Useful candidate, but compare it with alternatives before adopting.

Trust

Sandbox only
60

Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.

Audit

Needs review
76

A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.

OpenAgentSkill Trust Score v5

Human review before install

Run only in a sandbox and compare close alternatives before using it for real work.

CodexClaude CodeCursorOpenAgentSkill CLI

Stars

82 GitHub stars

Repo activity

82 stars, 2 forks

Maintenance

Pushed today

License

MIT

Install

npx skills add lin1111-1/academic-integrity-rewrite --skill academic-integrity-rewrite

Install safety

standard package or runtime install path

Permission surface

shell or command execution

Agent outcomes

No agent outcome data yet

Docs

Usable metadata, review docs

Risk summary

Review before production

  • The audit script's measurement regex may miss some uncommon unit notations (e.g., scientific notation, complex compound units), but this is explicitly acknowledged in the skill and manual review is recommended.
  • Quality score needs review
  • GitHub adoption: 82 GitHub stars
  • Stars/forks activity: 82 stars, 2 forks; issue activity unavailable in current metadata

Install readiness

Install path available

  • Install path is available
  • Repository evidence is available
  • License is declared
  • No Agent Proven outcome evidence yet

Agent-readable metadata

Machine-readable decision data for this skill.

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.

Open JSON

Suited tasks

  • Research agents workflows
  • Claude Code teams
  • builders willing to evaluate younger projects
  • Search sources

Suited agents

CodexClaude CodeCursorOpenAgentSkill CLICLI

Install decision

Command
npx skills add lin1111-1/academic-integrity-rewrite --skill academic-integrity-rewrite
Policy
review
Human review
yes

Trust and risk

Trust
60/100
Audit
76/100
Risk level
Needs review

Outcome loop

Endpoint
/api/agent/outcome
Event ID
resolve
Outcomes
5

Install command

npx skills add lin1111-1/academic-integrity-rewrite --skill academic-integrity-rewrite

Do not use when

  • teams that need a vendor-supported SLA
  • production agents without a repository review
  • The audit script's measurement regex may miss some uncommon unit notations (e.g., scientific notation, complex compound units), but this is explicitly acknowledged in the skill and manual review is recommended.
  • High-risk permission hints: Shell or command execution
  • No explicit handling for non-UTF8 encodings in plain text files, though most modern editors default to UTF-8.

Agent safety v2

48/100 · Avoid automatic install

Experimentalreview

Sparse or mixed signals. Useful for discovery, but not for autonomous installation.

Test manually in an isolated workspace and compare against safer alternatives.

Resolve via API

high

Shell or command execution

Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.

medium

Network access

Skill likely fetches remote pages, APIs, repositories, or external services.

medium

Filesystem access

Skill may read or write project files, documents, generated artifacts, or local workspace state.

  • High-risk permission hints: Shell or command execution
  • The audit script's measurement regex may miss some uncommon unit notations (e.g., scientific notation, complex compound units), but this is explicitly acknowledged in the skill and manual review is recommended.

Install targets

Install this skill in your agent workflow

Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.

skill install

OpenAgentSkill CLI

Resolve policy, run the source installer safely, and report a verified install receipt.

$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install lin1111-1-academic-integrity-rewrite

Agent resolve plan

Let an agent verify fit before installing.

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 text plan

Agent should check

  • Task fit and alternatives from Resolve API.
  • Audit score, trust score, and safety policy warnings.
  • Install target compatibility for Codex, Claude Code, Cursor, or CLI.

Copy prompt

Task: Use academic-integrity-rewrite in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20academic-integrity-rewrite%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/lin1111-1-academic-integrity-rewrite/install
Install command: npx skills add lin1111-1/academic-integrity-rewrite --skill academic-integrity-rewrite
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.

Agent handoff

Give an agent the install path, not another directory page.

Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.

Open install API

Agent prompt

Use academic-integrity-rewrite for this task. Review https://www.openagentskill.com/api/skills/lin1111-1-academic-integrity-rewrite/install, then install with: npx skills add lin1111-1/academic-integrity-rewrite --skill academic-integrity-rewrite

Registry metadata

Agent-readable profile for automatic skill selection.

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.

Open manifest

Agent fit

65/100

Research agents

Platforms

Claude Code

Audit report

Needs review · 76/100

A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.

View audit reportView eval report

Agent decision cockpit

Fallback candidate for Research agents

Prototype with this skill first; keep a fallback candidate ready.

65
Readiness
Prototype
Stage

Role in stack

Fallback candidate

Primary fit

Research agents

Trust label

Prototype first

Install path

Command ready

Use when

  • Research agents workflows
  • Claude Code teams
  • builders willing to evaluate younger projects

Evidence

  • recent repository activity
  • install command or GitHub repo available
  • 66/100 quality profile
  • 1 OpenAgentSkill engagement events

review first

  • The audit script's measurement regex may miss some uncommon unit notations (e.g., scientific notation, complex compound units), but this is explicitly acknowledged in the skill and manual review is recommended.

Implementation path

  1. 1Install it in a sandbox agent and run one Research agents task end to end.
  2. 2Compare output quality, latency, and failure behavior against at least one alternative.
  3. 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.

Trust profile

Sandbox only

Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.

60
OpenAgentSkill Trust Score

GitHub adoption

CHECK

82 GitHub stars

Stars/forks activity

CHECK

82 stars, 2 forks; issue activity unavailable in current metadata

Recent maintenance

PASS

Pushed today

License clarity

PASS

MIT

Good signals

  • AI review approved
  • Install path is available
  • Repository evidence is available
  • Recently maintained repository
  • Install command has no obvious high-risk pattern
  • Outcome loop is ready but needs first real agent run

Review before install

  • The audit script's measurement regex may miss some uncommon unit notations (e.g., scientific notation, complex compound units), but this is explicitly acknowledged in the skill and manual review is recommended.
  • Quality score needs review
  • GitHub adoption: 82 GitHub stars
  • Stars/forks activity: 82 stars, 2 forks; issue activity unavailable in current metadata
  • No real agent outcome reports yet
  • Human review required before unattended installation

Recommended action

Run only in a sandbox and compare close alternatives before using it for real work.

Quality profile

Promising candidate for agent workflows

Useful candidate, but compare it with alternatives before adopting.

66
GitHub stars
82
Freshness
Today
Install ready
Yes
License
MIT
Review before install: The audit script's measurement regex may miss some uncommon unit notations (e.g., scientific notation, complex compound units), but this is explicitly acknowledged in the skill and manual review is recommended.

Workflow fit

Use this skill in these scenarios

Workflow fit

Add it to a complete workflow

Alternative shortlist

Compare before you install

Similar skills that may fit this task.

Compare all

Overview

--- name: academic-integrity-rewrite description: Revise Chinese or English academic writing for lower unnecessary textual overlap while preserving meaning, evidence, numbers, equations, terminology, and citations. Use for 学术论文降重、查重后修改、重复段落重写、paraphrasing, similarity-report remediation, abstracts, literature reviews, methods, results, discussions, theses, and manuscripts in DOCX, Markdown, or plain text. Do not use to disguise plagiarism, fabricate sources, or evade academic-integrity review. ---

# Academic Integrity Rewrite

Rewrite from the research logic and evidence, not by replacing words sentence by sentence. Treat originality as clearer authorship and synthesis, never as detector gaming.

## Establish the task

1. Identify the target language, field, venue or style guide, editable sections, and any similarity report. 2. Distinguish the author's findings from cited ideas, standard definitions, methods that require precise wording, and text that must remain verbatim. 3. If the source or citation evidence is unavailable, mark claims for verification instead of inventing details. 4. State that no exact similarity score can be guaranteed because databases and algorithms differ.

## Triage before rewriting

Classify each flagged passage:

- **P0 — integrity or technical risk:** missing attribution, changed data, equations, labels, units, citations, or unsupported claims. Resolve first. - **P1 — reasoning risk:** source-by-source summary, weak synthesis, duplicated logic, overclaiming, or a mechanism not supported by the model or data. - **P2 — expression risk:** formulaic phrasing, noun stacking, repeated sentence frames, vague subjects, or unnecessary metadiscourse. - **P3 — presentation risk:** inconsistent terms, symbols, figure/table references, citation format, or typography.

Read [references/rewrite-methods.md](references/rewrite-methods.md) for section-specific strategies. Read [references/quality-gates.md](references/quality-gates.md) before final review.

## Build a protected fact ledger

Record, before drafting:

- every number, sign, range, unit, symbol, equation, boundary condition, and named method; - every citation marker and the claim it supports; - approved terminology, abbreviations, figure/table/equation numbers, and causal qualifiers; - direct quotations or legally/academically fixed language that must not be paraphrased.

Never silently change an item in this ledger. Flag contradictions or likely source errors for the author.

## Reconstruct the passage

1. Reduce the passage to an evidence map: purpose → method/evidence → result → interpretation → limitation. 2. Close the source text where practical and draft from that map. 3. Reorder claims by logic, combine redundant sentences, split overloaded sentences, and make the actor or evidence explicit. 4. Synthesize multiple sources by theme, agreement, disagreement, method, chronology, or research gap. Preserve attribution at claim level. 5. Prefer precise verbs and quantified statements. Remove empty frames such as “it is obvious,” “it can be seen,” and repeated announcements of what follows. 6. Preserve necessary technical terms. Do not force synonyms for established concepts.

## Validate

Run the deterministic audit when both original and revision are available:

```bash python scripts/audit_revision.py ORIGINAL REVISED ```

Use `--json PATH` for a machine-readable report. It compares numbers, common unit-bearing measurements, and citation markers. Treat its warnings as review prompts, not proof of plagiarism or correctness; uncommon or field-specific unit notation still requires manual review.

Then verify manually:

1. Compare the protected fact ledger against the revision. 2. Check every citation against its supported claim and, when possible, the primary source. 3. Check equations, terminology, abbreviations, units, and cross-references globally. 4. Confirm that interpretations do not exceed the method, model, or data. 5. Read the revision for natural academic flow and field-appropriate tone.

## Deliver

Return:

- the revised passage; - a concise change rationale grouped by logic, evidence, and expression; - a verification list for any unresolved facts, citations, or labels; - an audit summary stating whether numbers and citation markers were preserved and which long shared spans remain.

Do not claim guaranteed acceptance, guaranteed originality, or a guaranteed similarity percentage.

Technical details

Version
1.0.0
License
MIT
Last updated
Aug 24, 2026
Published
Aug 24, 2026

Decision snapshot

Fallback candidate

65
Ready
Prototype
Stage

recent repository activity

Audit

Install review

Install and adoption review

76
Needs review
Security
78/100
Maintenance
100/100
Install
92/100
Open full auditView eval report

Agent-proven evidence

Agent-proven evidence

Outcome reports after resolve, review, install, and one narrow run.

0
Proven
Needs first agent runAuto-install: review firstLast: Unknown
Success rate
Recent failure
Outcomes
0
Output quality
Failed
0
Not relevant
0
Installs
0
Risk blocked
0
Setup needed
0
Production
0

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

Add to agent workflow

Free and open source. Review the report before installing into production agents.

Growth loop

Share kit

X

Scenario-led draft for academic-integrity-rewrite, ready for a manual X post.

Curator note
academic-integrity-rewrite: Revise Chinese or English academic writing for lower unnecessary textual overlap while preser...

82 stars

https://www.openagentskill.com/skills/lin1111-1-academic-integrity-rewrite?ref=x
Open X draft
Optional reply with install command
Listing + install path for academic-integrity-rewrite:
https://www.openagentskill.com/skills/lin1111-1-academic-integrity-rewrite?ref=x

Install: npx skills add lin1111-1/academic-integrity-rewrite --skill academic-integrity-re...

Listing source

Registry indexed

Claimable

This listing was indexed from public sources and is not marked official until a maintainer claim is approved.

Creator
lin1111-1
Indexed by
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Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.

Claim this skill

Owner claim

Claim this skill listing

This Registry indexed listing is attributed to lin1111-1 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

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[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/lin1111-1-academic-integrity-rewrite?metric=listed&label=Listed)](https://www.openagentskill.com/skills/lin1111-1-academic-integrity-rewrite)
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Author

L

lin1111-1

@lin1111-1

Platform fit

Health signals

GitHub stars
82
Quality score
37/100
Last GitHub push
Aug 24, 2026
Framework hints
Unknown
OpenAgentSkill views
1
Install copies
0
Outbound clicks
0

Community signal

Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.

Trust & safety

Sandbox only

60
  • GitHub adoption82 GitHub starsCHECK
  • Stars/forks activity82 stars, 2 forks; issue activity unavailable in current metadataCHECK
  • Recent maintenancePushed todayPASS
  • License clarityMITPASS
  • README/SKILL.md completenessPublic metadata needs stronger README/SKILL.md contextINFO
  • Dependency/runtime riskcommand execution surfaceINFO