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VS-Enhanced Literature Review Strategist - Comprehensive support for multiple review methodologies Full VS 5-Phase process: Prevents Mode Collapse and presents creative search strategies Supports: Systematic Review (PRISMA 2020), Scoping Review (JBI/PRISMA-ScR), Meta-Synthesis, Realist Synthesis, Narrative Review, Rapid Review Use when: conducting any type of literature review, systematic reviews, meta-analyses, scoping reviews, finding prior research Triggers: literature review, PRISMA, systematic review, scoping review, meta-synthesis, realist synthesis, narrative review, rapid review

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Review changes since the last npm release through parallel change analysis, hands-on quality checks, and an overall release assessment. Receive a readiness verdict, blocking issues, version recommendations, and a draft changelog with compatibility concerns.

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• Assess readiness before an npm release
• Check breaking changes and migration needs
• Review version bump recommendations

Iteratively improve research by having Claude Code review code, results, and drafts while Codex implements fixes. Repeat until the assessment meets the stopping criteria or the round limit is reached, preserving feedback and unresolved issues.

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• Repeating research reviews and fixes before submission
• Checking whether claims match code and experiment results
• Tracking how reviewer concerns are addressed across rounds

Review a pull request using repository checks, verified code references, and current official documentation. Assess correctness, security, structure, and unnecessary code, then post one consolidated GitHub review with inline findings and an evidence-based verdict.

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• Review a pull request before merging
• Check code structure and unnecessary comments
• Verify dependency changes against official documentation

Produce honest product reviews and buying guides without fabricated first-hand experience, using disclosed evidence tiers: verified specs, owner-experience synthesis at scale, expert triangulation, and hands-on only when true. Use this skill whenever the user wants to write product reviews or buying guides without hands-on access, set up a review methodology, add evidence disclosure to review content, align reviews with Google's reviews system or FTC affiliate disclosure expectations, or decide when Review and Product schema are honest to use. Triggers on product review, buying guide, best-of list, review methodology, evidence basis, hands-on testing, we tested, affiliate review site, review disclosure, methodology block, original research, reviews system. Also triggers when review content claims testing that did not happen, or when an affiliate site needs a trust mechanism that survives scrutiny.

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Drive a PR to an approved code review by looping OCR's multi-agent review and address steps. Runs /ocr:review then /ocr:address repeatedly until the review verdict is APPROVE, then one final /ocr:address for leftover suggestions, posting every review and every address round to the GitHub PR as comments. Use when the user asks to 'review and address in a loop', 'iterate review until approved', 'auto review-and-fix this PR', 'loop /ocr:review and /ocr:address', or to take a changeset all the way to a clean APPROVE with the default reviewer team. Wraps the /ocr:review (.ocr/commands/review.md) and /ocr:address (.ocr/commands/address.md) skills; needs a feature branch with an open GitHub PR and the gh CLI for posting.

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使用共享的OpenClaw审查流程和辅助脚本检查代码，同时遵循目标仓库的专属要求。实际审查流程来自统一安装的共享技能。

• 按统一流程审查代码
• 检查仓库专属审查要求
• 集中更新共享审查流程

Review code changes with several independent reviewers working in parallel, then receive organized findings. Request a quick or thorough review, choose to hand off fixes, or run without interaction when another workflow or CI job initiates the review.

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• Review code changes from multiple independent perspectives
• Choose a quick or thorough review
• Receive findings with fixes handed off

Review Git changes with the ocr command-line tool and a configured AI model. Get line-level findings grouped by severity for working changes, commits, or branch comparisons, with code fixes applied when explicitly requested.

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• Reviewing changes before a commit
• Checking a pull request or branch comparison
• Inspecting a specific commit for issues

Review code changes from three critical perspectives: production failures, maintainability, and security. Get a consolidated report that ranks findings by severity and provides merge guidance, helping examine assumptions that an ordinary self-review may overlook.

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• Reviewing a pull request before merging
• Getting a second opinion on AI-written code
• Checking authentication or data access code

Plan revenue growth for B2B SaaS businesses by analyzing sales opportunities, pricing, customer retention, and sales capacity. Develop scenario forecasts, churn intervention plans, hiring models, and revenue reporting for board discussions.

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• Forecast next quarter’s revenue
• Analyze churn and expansion revenue
• Review pricing and packaging

Run Polly AI Review and Open Code Review repeatedly on a pull request. Track each finding, fix relevant issues, document justified dismissals, and verify that review evidence and recorded decisions cover the latest commit.

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• Resolving findings from two automated PR reviewers
• Reviewing each new commit after fixes
• Recording evidence for dismissed or duplicate findings

Ask external AI command-line tools to independently review a development phase plan. Collect feedback by reviewer in REVIEWS.md, then feed the results into GSD planning to support revisions.

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• Getting independent AI reviews before implementation
• Comparing feedback from multiple AI reviewers
• Saving structured review feedback in a document

Review medium to large code changes using checks selected for the actual patch. Analyze the change and surrounding code, assign focused reviews by function, file, or feature, and combine findings with locations, confidence levels, and supporting evidence.

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• Reviewing patches of roughly 50 to 1,000 lines
• Checking risks specific to a changed feature
• Reviewing changes alongside callers and related implementations

Extract the same fields from a batch of contracts or other documents into a comparison spreadsheet. Each answer includes a source quote and location, while missing, ambiguous, and review-required information is clearly distinguished for human verification.

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• Compare contract clauses during M&A due diligence
• Audit vendor contracts using a shared set of fields
• Review dates and notice periods across a lease portfolio

Review code using shared OpenClaw instructions and a Python helper, while also following the target repository’s review requirements. This skill points to a common installation that supplies the actual review procedure.

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• Reviewing code with shared OpenClaw instructions
• Applying repository-specific review requirements
• Keeping shared review instructions up to date

Multi-perspective academic paper review with dynamic reviewer personas. Simulates 5 independent reviewers (EIC + 3 peer reviewers + Devil's Advocate) with field-specific expertise. Supports full review, re-review (verification), quick assessment, methodology focus, and Socratic guided modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review.

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Review code for bugs, security vulnerabilities, API misuse, consistency issues, simplicity problems, or test coverage gaps and low-value tests by running internal reviews and a peer review in parallel and returning combined findings. Single-concern with a type argument, or full review with no argument. Use when the user asks to "review my code", "full code review", "review my changes", "check for bugs", "scan for bugs", "review correctness", "security audit", "find vulnerabilities", "review security", "check API usage", "verify against docs", "check for cross-file duplication", "review consistency", "check for code reuse", "review simplicity", "find untested code", "find redundant tests", or "review test coverage".

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Drive a GitHub Copilot (or any bot reviewer) pull-request review to a clean pass without babysitting it: fix each finding in its own commit, reply to the review thread with the fix sha, resolve the thread, re-request the bot, and poll for the async re-review. Covers the thread node-id (PRRT_...) vs comment databaseId distinction, the resolveReviewThread GraphQL mutation, the copilot-pull-request-reviewer[bot] slug, and how to read the bot's verdict (COMMENTED plus a "human review recommended" banner is not a blocking finding). Use when Copilot has left review comments on your PR, when bot review threads must be closed out with an auditable fix-reply-resolve trail before merge, or when you need to verify that a re-review actually landed on the new HEAD rather than the old one.

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Simulate a Nature-style reviewer assessment from the referee perspective rather than an author rebuttal. Use when the user wants a pre-submission review, reviewer report, peer-review style critique, novelty/significance/technical soundness assessment, reviewer-style manuscript evaluation, 审稿人视角评估, 预审稿意见, or Nature reviewer report. Return 3 reviewer reports plus a cross-review synthesis, grounded only in the local Nature reviewer source basis. Also trigger on general pre-submission review requests during academic writing even without the word "Nature", such as getting a mock peer review for any journal, critiquing a draft as a reviewer would, assessing novelty/rigor before submission, and Chinese phrasings like 审稿人视角、模拟审稿、预审、帮我审一下论文、投稿前自审、审稿意见模拟、找论文问题.

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review-all を実行し、指摘内容をコードに反映、bun run c / bun run lint / bun test で自己検証し、CONVERGED/NOT_CONVERGED の収束判定付き完了レポートを /tmp/arima-review-fix-result.md に出力する。レビュー→修正→検証→レポートを一気通貫で行うスキル。スコープ引数は /review-all と同じ（wt / PR #N / vs:<branch> / range / ファイル列挙）。review-fix-loop からの自動呼び出し（mode=non-interactive）にも対応。Use when user says 'レビューして直して', 'review and fix', '自動修正', 'レビュー反映', or when invoked by review-fix-loop.

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Review a GitNexus pull request for production readiness with seven coordinated reviewer agents. Combine their findings and have a final critic check the draft, producing a review without editing code or posting results.

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• Reviewing a GitNexus pull request before production use
• Combining findings from multiple reviewer agents
• Checking a review draft before finalizing it

Coordinate GitHub pull request reviews by assigning comment triage and code changes to dedicated sub-agents. Repeat the process, track decisions and progress, and reply to and resolve threads as fixes are completed.

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• Work through outstanding pull request review comments
• Separate required fixes from items outside the pull request scope
• Repeat review and implementation until actionable items are cleared

Collect and validate the review state of a GitHub pull request, then generate a readable Markdown report, a text summary, and a list of items to address before review triage begins.

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• Collecting the current review state of a pull request
• Summarizing unresolved threads and review comments
• Preparing review items for subsequent triage