- 📄 SKILL.md
prompt-master
Generates optimized prompts for any AI tool.
Generates optimized prompts for any AI tool.
Generates OpenChart (https://github.com/tryopendata/openchart) chart, table, graph, and sankey specs from data, and guides editorial design decisions. Use when creating visualizations, building charts, rendering data tables, generating VizSpec JSON, creating network graphs, building sankey/flow diagrams, answering questions about OpenChart types and encoding rules, or making design decisions about chart type selection, color strategy, typography, annotations, and editorial framing. Also covers custom D3.js infographics for cases beyond declarative specs. --- # Data Visualization with OpenChart **Core concept:** Write a VizSpec JSON object, render with `<Chart>` / `<DataTable>` / `<Graph>` / `<Sankey>` (React/Vue/Svelte) or `createChart()` / `createTable()` / `createGraph()` / `createSankey()` (vanilla JS). The engine validates, compiles, and renders. Specs are plain JSON, no imperative drawing. See https://github.com/tryopendata/openchart for the rendering engine. **CSS is required.** OpenChart's stylesheet must be loaded for proper rendering (chrome, tables, tooltips, brand watermark). Framework imports handle this automatically, but CDN/standalone HTML needs an explicit `<link>`: ```html <link rel="stylesheet" href="https://esm.sh/@opendata-ai/openchart-vanilla/styles.css"> ``` See [rendering reference](references/rendering.md) for details. ## Chart Selection Decision Tree ``` Single value to highlight -> Use chrome.title as a big number display Temporal x-axis column? -> 1 series: line | 2-5 series: line + color | 6+: filter to top 5 Categorical + numeric? -> Ranked list: bar (horizontal) | Periodic (Q1, Jan): bar (vertical) | 2-6 composition: arc Two numeric columns? -> point (optional size/color for 3rd/4th dims) Categorical + series + num? -> stacked bar (use color for series) Distribution/spread? -> circle (strip plot) Nodes + edges / network? -> graph (force/radial/hierarchical layout) Flow between stages? -> sankey
Restored placeholder content.
Capture current session transcript to workspace history. Use at session end or when preserving conversation context.
Local-first cross-harness memory for agents. Syke observes activity across supported harnesses, keeps a current memex in context, and gives agents `syke ask`, `syke context`, and `syke record` for continuity across sessions.
Remove signs of AI-generated writing from academic medical papers. Use when editing or reviewing manuscripts to make them sound more natural and professionally written. Based on Wikipedia's "Signs of AI writing" guide, adapted for medical literature.
Query and manage Apple Calendar on macOS via `icalBuddy` (read) and AppleScript (`osascript`) for event creation. Use when users ask about upcoming events or adding calendar events.
AWS cloud security testing covering S3 misconfiguration, IAM abuse, Lambda SSRF, IMDSv1/v2 exploitation, and STS token theft
Security monitor for scrapingbee-cli. Monitors audit log for suspicious activity. Stops unauthorized schedules. ALWAYS active when scrapingbee-cli is installed.
Design A/B and multivariate tests. Use when: sample size calculation, testing hypothesis, CRO experimentation.
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.
Executes multi-step research-plan-implement-review workflows using mnemonic for workflow artifacts. Triggers on multi-step feature or bugfix work, subagent handoffs, plan-heavy tasks, or any work needing structured RPIR artifacts with explicit handoffs and consistent role/relationship conventions.
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: