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Import Skills

Composite Most Downloads Most Likes Most Comments Newest
NoesisVision NoesisVision
from GitHub Research & Analysis
  • 📄 SKILL.md
benchmark coding create

nasde-benchmark-creator

Create coding agent benchmarks for evaluation with nasde. Use this skill when the user wants to: - Create a new benchmark project (set of tasks for evaluating coding agents) - Add tasks to an existing benchmark - Create or modify agent variants (configurations that control agent behavior) - Set up assessment dimensions and scoring criteria - Verify that a new benchmark's Docker environment and tests work Even if the user doesn't say "benchmark" — if they're talking about creating coding challenges for AI agents or setting up evaluation criteria, this skill applies. --- # NASDE Benchmark Creator Create and configure coding agent benchmarks for evaluation with `nasde`. A benchmark is a set of coding tasks that AI agents solve inside isolated Docker containers, scored both by functional tests (pass/fail) and by an LLM-as-a-Judge architecture assessment. ## Critical: line endings on Windows (read this first) Benchmark scripts execute inside **Linux** sandboxes (Docker, Daytona). If `tests/test.sh`, `solution/solve.sh`, or `environment/Dockerfile` are checked out with **CRLF** line endings (the Windows git default when `core.autocrlf=true` and there is no `.gitattributes`), every trial fails immediately with: ```

⬇0 ❤7 16 days ago · Uploaded Detail →
ngvoicu ngvoicu
from GitHub Development & Coding
  • 📁 .claude-plugin/
  • 📁 .cursor-plugin/
  • 📁 agents/
  • 📄 .gitignore
  • 📄 AGENTS.md
  • 📄 CLAUDE.md
spec specs coding

specmint-core

Persistent spec management for AI coding workflows. Use this skill when the user explicitly mentions specs, forging, or structured planning: says "forge", "forge a spec", "write a spec for X", "create a spec", "plan X as a spec", "resume", "what was I working on", "spec list/status/pause/switch/activate", "implement the spec", "implement phase N", "implement all phases", "generate openapi", or exits plan mode (offer to save as a spec). Also trigger when a `.specs/` directory exists at session start. Do NOT trigger on general feature requests, coding tasks, or questions that don't mention specs or forging — those are normal coding tasks, not spec management. --- # Spec Mint Core Turn ephemeral plans into structured, persistent specs built through deep research and iterative interviews. Specs have phases, tasks, acceptance criteria, a registry, resume context, a decision log, and a deviations log. They live in `.specs/` at the project root and work with any AI coding tool that can read markdown. Whether `.specs/` is committed is repository policy. Respect `.gitignore` and the user's preference for tracked vs local-only spec state. ## Critical Invariants 1. **Single-file policy**: Keep this workflow in one `SKILL.md` file. 2. **Canonical paths**: - Registry: `.specs/registry.md` - Per-spec files: `.specs/<id>/SPEC.md`, `.specs/<id>/research-*.md`, `.specs/<id>/interview-*.md` 3. **Authority rule**: `SPEC.md` frontmatter is authoritative. Registry is a denormalized index for quick lookup. 4. **Active-spec rule**: Target exactly one active spec at a time. 5. **Parser policy**: Use best-effort parsing with clear warnings and repair guidance instead of hard failure on malformed rows. 6. **Progress tracking is sacred**: After completing any task, immediately update SPEC.md (checkbox, `← current` marker, phase marker) AND registry.md (progress count, date). Then re-read both files to verify the edits landed correctly. Never move to the next task without updating both files.

⬇0 ❤6 1 month ago · Uploaded Detail →

Skill File Structure Sample (Reference)

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

SKILL.md Requirements

├─ ⭐ 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

Why SkillWink?

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.

Keyword Search Version Updates Multi-Metric Ranking Open Standard Discussion

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.

FAQ

Everything you need to know: what skills are, how they work, how to find/import them, and how to contribute.

1. What are Agent Skills?

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.

2. How do Skills work?

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.

3. How can I quickly find the right skill?

Use these three together:

  • Semantic search: describe your goal in natural language.
  • Multi-filtering: category/tag/author/language/license.
  • Sort by downloads/likes/comments/updated to find higher-quality skills.

4. Which import methods are supported?

  • Upload archive: .zip / .skill (recommended)
  • Upload skills folder
  • Import from GitHub repository

Note: file size for all methods should be within 10MB.

5. How to use in Claude / Codex?

Typical paths (may vary by local setup):

  • Claude Code：~/.claude/skills/
  • Codex CLI：~/.codex/skills/

One SKILL.md can usually be reused across tools.

6. Can one skill be shared 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.

7. Are these skills safe to use?

Some skills come from public GitHub repositories and some are uploaded by SkillWink creators. Always review code before installing and own your security decisions.

8. Why does it not work after import?

Most common reasons:

  • Wrong folder path or nested one level too deep
  • Invalid/incomplete SKILL.md fields or format
  • Dependencies missing (Python/Node/CLI)
  • Tool has not reloaded skills yet

9. Does SkillWink include duplicates/low-quality skills?

We try to avoid that. Use ranking + comments to surface better skills:

  • Duplicate skills: compare differences (speed/stability/focus)
  • Low quality skills: regularly cleaned up