Manage Paperclip AI companies, agents, issues, projects, goals, routines, costs, and secrets via REST API. Use when creating companies, hiring agents, assigning tasks, managing budgets, approving hires, or checking dashboards on a Paperclip instance.
Design, validate, scaffold, and visualize multi-agent topologies using the .at language
Use when analyzing packet captures or live network traffic with Wireshark MCP; choose the right workflow for triage, security hunting, incident response, troubleshooting, or CTF work, then produce evidence-backed findings with exact filters, streams, frames, and next steps.
Create Excalidraw diagram JSON files that make visual arguments. Use when the user wants to visualize workflows, architectures, or concepts.
Map requirements (PRD/user stories/AC) to comprehensive test coverage using a traceability matrix (RTM). Outputs coverage gaps, risks, test levels, prioritization, automation candidates, and change-impact notes. Designed for QA/Test Architect workflows.
Use for DataLion workflows such as listing, reading, creating, or editing projects, inspecting data sources, importing Excel or CSV data, working with reports and report tabs and codebooks, reading chart tables, or coordinating dashboard and export work through a configured datalion MCP server and related API or UI paths.
Install and configure TMA1 local observability. Use when the user says: install tma1, setup observability, monitor my agent, track token usage, set up telemetry.
Interactively create a new Claude Code skill and add it to the elastic-docs-skills catalog. Use when the user wants to generate a new skill, scaffold a slash command, or build automation for docs tasks.
Set up a complete agent team with file-based planning for complex multi-agent projects.
Design agent system prompts, parallel architectures, and methodological guardrails for data science decision-packs. Use when creating orchestrator, subagent, or parallel agent systems for analytical workflows. Covers anti-fabrication rules, epistemic humility, when to stop, conflict detection, uncertainty reporting, retry protocols, prompt design principles, and the decision-lab runtime mechanics.
Persistent memory for coding agents. Query past decisions and learnings before starting work. Lerim watches your sessions, extracts what matters, and makes it available across every future session.
>-
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:
