Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. When Claude needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks
Use when working with crit CLI commands, .crit.json files, addressing review comments, leaving inline code review comments, sharing reviews via crit share/unpublish, pushing reviews to GitHub PRs, or pulling PR comments locally. Covers crit comment, crit share, crit unpublish, crit pull, crit push, .crit.json format, and resolution workflow.
Analyze and address unresolved feedback on a GitHub pull request. Use when the user has received PR review comments and wants to systematically address each piece of feedback, or when the user mentions PR feedback, review comments, or addressing reviewer concerns.
This skill should be used when someone needs to generate a brag document from GitHub activity, set up reflect for the first time, run reflect to fetch contributions, configure a GitHub token for reflect, filter contributions by organization or repository, choose between OpenAI and Anthropic providers, understand reflect output files, troubleshoot reflect not working, or debug brag doc errors. --- # Reflect Reflect is a CLI tool that fetches GitHub activity -- merged pull requests, closed issues, and PR reviews -- and uses LLM APIs to generate professional brag documents for performance reviews. It connects to the GitHub GraphQL API via Octokit to retrieve contribution data, then optionally passes that data through an LLM provider (OpenAI or Anthropic) to produce summarized and narrative-format documents. All output is written as structured Markdown files suitable for self-assessments, promotion packets, and manager reviews. ## First-Time Setup ### Prerequisites Ensure the following are available before running Reflect
automated reviewers, fetch comments, fix or pushback, reply, resolve threads.
Use when preparing commit messages, pull request titles, or summary comments for this repository. Enforce `type(scope): subject` without `[codex]`, using one of `feat`, `fix`, `test`, `chore`, or `docs`.
automated reviewers, fetch comments, fix or pushback, reply, resolve threads.
Generate structured A-share market commentary for three fixed trading sessions using supplied market data: within 30 minutes after market open, after midday close, and after market close. Use this skill when the user wants factual market observation, intraday commentary, or end-of-day review content based on real A-share inputs. Do not use it for stock picking, trading advice, or fabricated commentary without data.
Parse self-review XML feedback and execute the review comments as organized tasks
Post Q&A entries from office hours writeups as comments to a GitHub Discussion. Use when the user wants to post writeup content to a discussion thread.
Triages unresolved PR review comments using gh-pr-reviews. Analyzes code context and classifies each comment as Agree / Partially Agree / Disagree. Walks through each comment one-by-one, asking the user what action to take. Use when the user wants to triage, review, or analyze unresolved PR comments.
Review and resolve PR comments from GitHub. Validates each comment, fixes legitimate issues.
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:
