> Override for Codex users who want **Gemini**, not a second Codex agent, to act as the reviewer. Install this package **after** `skills/skills-codex/*`.
Skills(SKILL.md)は、AIエージェント(Claude Code、Cursor、Codexなど)に特定の能力を追加するための設定ファイルです。
詳しく見る →> Override for Codex users who want **Gemini**, not a second Codex agent, to act as the reviewer. Install this package **after** `skills/skills-codex/*`.
> Override for Codex users who want **Gemini**, not a second Codex agent, to act as the reviewer. Install this package **after** `skills/skills-codex/*`.
Use when main results pass result-to-claim (`claim_supported = yes` or `partial`) and ablation studies are needed for paper submission. A secondary Codex agent designs ablations from a reviewer's perspective; the local executor reviews feasibility and implements.
Communications-domain literature review and related-work search with database-aware source control. Use when the task is about communications, wireless, networking, satellite/NTN, Wi-Fi, cellular, transport protocols, congestion control, routing, scheduling, MAC/PHY, rate adaptation, channel estimation, beamforming, or communication-system research and the user wants papers, prior art, a survey, related work, or a landscape summary. Prioritize IEEE Xplore and ScienceDirect, prefer formal publications over preprints, and separate foundational work from recent progress.
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Design clinical studies and report using CONSORT, STROBE guidelines
Multi-agent system for biomedical literature review and synthesis
Structured frameworks for market sizing, competitive analysis, and strategic ...
Search open access journals and articles in the DOAJ directory
Guide to preprint servers across scientific disciplines
Multi-source exhaustive literature search across academic databases
Search PLOS open access journals with full-text Solr-powered API
Access Latin American and developing world research via SciELO API
Construct rigorous systematic search strategies for literature reviews
Claude Code template for LaTeX, Beamer, and R research workflows
AI-driven multi-agent research assistant for end-to-end studies
13 deep research & systematic reviews skills. Trigger: systematic reviews, multi-source synthesis, comprehensive literature surveys. Design: multi-step research protocols with quality assessment and evidence grading.
Structured methodology for conducting exhaustive multi-source investigations
Claude Code-driven autonomous AI Scientist for discovery
Scoping review methodology for broad evidence mapping
Systematic review methodology with PRISMA and evidence synthesis
Prepare and justify research grant budgets across funding agencies
Navigate NSF grant applications, program selection, and strategies
Plan and manage systematic literature reviews with Parsifal platform
Simulate human research communities with multi-agent AI collaboration
Tools and pipelines for automating systematic literature reviews
8 peer review skills. Trigger: reviewing manuscripts, comparing papers, quality assessment. Design: systematic review criteria, evaluation rubrics, and automated review tools.
AI-assisted peer review tools, workflows, and quality standards
Automate systematic literature reviews with LatteReview AI agents
Structured framework for writing peer review reports and paper critiques
Conduct thorough, constructive peer reviews and evaluate research papers
Write effective rebuttals to reviewer comments for journal submissions
Craft effective point-by-point reviewer response letters
Write literature reviews and survey papers from collected papers
Deep dual-mode reading of academic papers from PDF or URL sources
Structure and write comprehensive literature reviews for any field
Write ML/AI research papers targeting NeurIPS, ICML, and ICLR venues
Write effective point-by-point responses to peer reviewer comments for revisions
Curated tools and techniques for scientific writing beyond LaTeX
Review and polish LaTeX research papers for clarity and style
Remove AI writing patterns from prose. Use when drafting, editing, or reviewing text to eliminate predictable AI tells.
'Analyze Datadog error logs for Packmind production services (API, MCP server, Frontend), group them into patterns, perform root cause analysis against the codebase, and produce a structured bug report. This skill should be used when investigating production errors, triaging bugs, auditing service health, or performing periodic error reviews. Also triggers when the user mentions Datadog, production logs, error analysis, prod issues, service health, or asks about what errors are happening in prod. Also triggers on references to specific Datadog service names like api-proprietary, mcp-proprietary, or frontend-proprietary.'
Use SwarmVault when the user needs a local-first knowledge vault that writes durable markdown, graph, search, dashboard, review, and MCP artifacts to disk from books, notes, transcripts, exports, datasets, slide decks, files, URLs, code, and recurring source workflows.
'Stewardship virtues (Care, Curiosity, Humility, Diligence) for plugins.'
Capture and retrieve PR review knowledge in project memory palaces.
'Evaluate API surface design, consistency, documentation, and exemplar alignment'
'Scope-focused PR review with requirements validation and backlog triage'
GitHubのプルリクエスト(PR)を作成する際に使用します。変更のコミット、プッシュ、PR作成を含む完全なワークフローを日本語で実行します。「PRを作って」「プルリクエストを作成」「pull requestを作成」などのリクエストで自動的に起動します。
Security intelligence for code analysis. Detects SQL injection, XSS, CSRF, authentication issues, crypto failures, and more. Actions: scan, analyze, fix, audit, check, review, secure, validate, sanitize, protect. Languages: JavaScript, TypeScript, Python, PHP, Java, Go, Ruby. Frameworks: Express, Django, Flask, Laravel, Spring, Rails. Vulnerabilities: SQL injection, XSS, CSRF, authentication bypass, authorization issues, command injection, path traversal, insecure deserialization, weak crypto, sensitive data exposure. Topics: input validation, output encoding, parameterized queries, password hashing, session management, CORS, CSP, security headers, rate limiting, dependency scanning.
Enhanced git operations using lazygit, gh (GitHub CLI), and delta. Triggers on: stage changes, create PR, review PR, check issues, git diff, commit interactively, GitHub operations, rebase, stash, bisect.