Review pull requests for the MiniMax Skills repository. Use when reviewing PRs, validating new skill submissions, or checking existing skills for compliance. Run the validation script first for hard checks, then apply quality guidelines for content review. Triggers: PR review, pull request, validate skill, check skill.
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.
Interacts with live Hunk diff review sessions via CLI. Inspects review focus, navigates files and hunks, reloads session contents, and adds inline review comments. Use when the user has a Hunk session running or wants to review diffs interactively.
Incorporate code review feedback — make code changes, commit with review trailers, update disposition table, and request re-review if needed. Mirrors plan-incorporate for code reviews.
This skill should be used when a user asks for a code review, feedback on a PR or MR, diff assessment, or says things like 'can you review my changes', 'look at this diff', 'is this ready to merge', 'check my code', 'review this branch', 'what do you think of these changes', or 'LGTM check'. Covers correctness, tests, performance, security, and architecture feedback on pull/merge requests or raw diffs from any platform (GitHub, GitLab).
Use when the user asks to review code, check for issues, or says "review", "审查", "检查代码
Review Markdown documents using the MRSF (Sidemark) sidecar format. Use when asked to review, comment on, or provide feedback on Markdown files. Adds structured, anchored review comments via the MRSF MCP server.
Run a local code review against project architecture rules and quality standards. Use when the user asks to review code, check for violations, or audit changes.
Project initialization, idea tracking, and GitHub setup. Use when starting a new project, reviewing deferred ideas, or bootstrapping GitHub labels and project boards.
审查代码、diff、提交或当前 git 改动，重点发现 bug、行为回归、边界条件遗漏、安全风险、性能问题和缺失测试。当用户提到 code review、review 这段代码、帮我看看改动有没有问题、审查 PR/提交时使用；不要用于单纯解释代码或直接实现需求。
Orchestrate multi-agent teams with defined roles, task lifecycles, handoff protocols, and review workflows. Use when: (1) Setting up a team of 2+ agents with different specializations, (2) Defining task routing and lifecycle (inbox → spec → build → review → done), (3) Creating handoff protocols between agents, (4) Establishing review and quality gates, (5) Managing async communication and artifact sharing between agents.
Multi-LLM peer review — send plans, ideas, or code to GPT (via OpenAI Codex CLI) and Gemini (via Gemini CLI) for structured peer review with cross-examination, then cherry-pick feedback. Decision Packet v2 with tiered output (Ship Blocker / Before Next Sprint / Backlog), dependency arrows, effort estimates, conflict flags, confidence scores, and JSON export with formal schema validation. Tie-breaker model resolves HIGH CONFIDENCE deadlocks. Supports review, idea, redteam, debate, premortem, advocate, refactor, deploy, api, perf, diff, quick, gate, delegate, help, history, status, and result modes. Supports parallel multi-mode dispatch (--modes redteam,deploy,perf) with collision detection. Review gate mode validates Claude's own output via GPT/Gemini before proceeding. Delegate mode hands off implementation tasks to external models with write permissions. Background execution (--background) for async reviews with job management (status/result). Session resumability (--resume) for continuing prior reviews across turns. Use this skill whenever the user wants a second opinion from other AI models, wants to brainstorm with multiple perspectives, needs adversarial analysis, wants to stress-test a plan, review a code diff, get deployment readiness feedback, API design review, performance analysis, validate Claude's output, delegate coding tasks, or mentions peer review, brainstorm, or multi-LLM feedback. Supports --rounds N, --verbose, --quiet, --gpt-model, --gemini-model, --steelman, --iterate, --json, --modes, --effort, --background, and --resume flags. Model aliases (spark, mini, flash, pro) for quick model selection. Falls back to GitHub Copilot CLI if Codex CLI is unavailable.
skill-sample/ ├─ SKILL.md ⭐ Required: skill entry doc (purpose / usage / examples / deps) ├─ manifest.sample.json ⭐ Recommended: machine-readable metadata (index / validation / autofill) ├─ LICENSE.sample ⭐ Recommended: license & scope (open source / restriction / commercial) ├─ scripts/ │ └─ example-run.py ✅ Runnable example script for quick verification ├─ assets/ │ ├─ example-formatting-guide.md 🧩 Output conventions: layout / structure / style │ └─ example-template.tex 🧩 Templates: quickly generate standardized output └─ references/ 🧩 Knowledge base: methods / guides / best practices ├─ example-ref-structure.md 🧩 Structure reference ├─ example-ref-analysis.md 🧩 Analysis reference └─ example-ref-visuals.md 🧩 Visual reference
More Agent Skills specs Anthropic docs: https://agentskills.io/home
├─ ⭐ Required: YAML Frontmatter (must be at top) │ ├─ ⭐ name : unique skill name, follow naming convention │ └─ ⭐ description : include trigger keywords for matching │ ├─ ✅ Optional: Frontmatter extension fields │ ├─ ✅ license : license identifier │ ├─ ✅ compatibility : runtime constraints when needed │ ├─ ✅ metadata : key-value fields (author/version/source_url...) │ └─ 🧩 allowed-tools : tool whitelist (experimental) │ └─ ✅ Recommended: Markdown body (progressive disclosure) ├─ ✅ Overview / Purpose ├─ ✅ When to use ├─ ✅ Step-by-step ├─ ✅ Inputs / Outputs ├─ ✅ Examples ├─ 🧩 Files & References ├─ 🧩 Edge cases ├─ 🧩 Troubleshooting └─ 🧩 Safety notes
Skill files are scattered across GitHub and communities, difficult to search, and hard to evaluate. SkillWink organizes open-source skills into a searchable, filterable library you can directly download and use.
We provide keyword search, version updates, multi-metric ranking (downloads / likes / comments / updates), and open SKILL.md standards. You can also discuss usage and improvements on skill detail pages.
Quick Start:
Import/download skills (.zip/.skill), then place locally:
~/.claude/skills/ (Claude Code)
~/.codex/skills/ (Codex CLI)
One SKILL.md can be reused across tools.
Everything you need to know: what skills are, how they work, how to find/import them, and how to contribute.
A skill is a reusable capability package, usually including SKILL.md (purpose/IO/how-to) and optional scripts/templates/examples.
Think of it as a plugin playbook + resource bundle for AI assistants/toolchains.
Skills use progressive disclosure: load brief metadata first, load full docs only when needed, then execute by guidance.
This keeps agents lightweight while preserving enough context for complex tasks.
Use these three together:
Note: file size for all methods should be within 10MB.
Typical paths (may vary by local setup):
One SKILL.md can usually be reused across tools.
Yes. Most skills are standardized docs + assets, so they can be reused where format is supported.
Example: retrieval + writing + automation scripts as one workflow.
Some skills come from public GitHub repositories and some are uploaded by SkillWink creators. Always review code before installing and own your security decisions.
Most common reasons:
We try to avoid that. Use ranking + comments to surface better skills:
