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Import Skills

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QSong-github QSong-github
from GitHub Databases & Storage
  • 📄 __init__.py
  • 📄 adrecs_skill.py
  • 📄 example.py
drug adrecs dataframe

ADReCS-query

Query the ADReCS (Adverse Drug Reaction Classification System) v3.3 database. Use whenever the user asks about adverse drug reactions, drug safety profiles, ADR classification, ADR severity/frequency, or wants to look up any entity (drug name, BADD Drug ID, DrugBank ID, ATC code, CAS RN, PubChem CID, KEGG ID, ADR term, ADReCS ID, MedDRA code, MeSH ID) in ADReCS. --- # ADReCS Query Skill Search ADReCS v3.3 records by any entity. Auto-detects type by prefix: | Input Pattern | Detected As | Example | |---|---|---| | `BADD_D00142` | BADD Drug ID | exact on drug_id column | | `DB00945` | DrugBank ID | resolved via Drug_information | | `A02BC01` | ATC code | resolved via Drug_information | | `50-78-2` | CAS RN | resolved via Drug_information | | `CID2244` or bare digits | PubChem CID | resolved via Drug_information | | `D00109` (5-digit) | KEGG ID | resolved via Drug_information | | `08.06.02.001` | ADReCS ID | substring on ADReCS_ID column | | `10003781` (8-digit) | MedDRA code | resolved via ADR_ontology | | `D######` (6+ digit) | MeSH ID | resolved via ADR_ontology | | anything else | free text | substring on drug_name OR ADR_term | ## API | Function | Input | Returns | |---|---|---| | `load_drug_adr(path)` | txt path | DataFrame (Drug–ADR pairs) | | `load_drug_info(path)` | xlsx path | DataFrame (drug metadata) | | `load_adr_ontology(path)` | xlsx path | DataFrame (ADR hierarchy) | | `search(entity)` | single entity string | DataFrame of matching Drug–ADR rows | | `search_batch(entities)` | list of entity strings | dict[str, DataFrame] | | `summarize(hits, entity)` | DataFrame + label | compact LLM-readable text | | `to_json(hits)` | DataFrame | list[dict] | ## Usage See `if __name__ == "__main__"` block in `62_ADReCS.py` for runnable examples covering: drug name lookup, BADD Drug ID, DrugBank ID, ADR term, ADReCS ID prefix, batch search, and JSON output. ## Data - **Source**: ADReCS v3.3 — [https://www.bio-add.org/ADReCS/](https://www.bio-add.org/ADReCS/) - **Primary

⬇0 ❤127 8 days ago · Uploaded Detail →
nowork-studio nowork-studio
from GitHub Tools & Productivity
  • 📁 evals/
  • 📁 references/
  • 📄 SKILL.md
ads account audit

ads-audit

Google Ads account audit and business context setup. Run this first — it gathers business information, analyzes account health, and saves context that all other ads skills reuse. Trigger on "audit my ads", "ads audit", "set up my ads", "onboard", "account overview", "how's my account", "ads health check", "what should I fix in my ads", or when the user is new to AdsAgent and hasn't run an audit before. Also trigger proactively when other ads skills detect that business-context.json is missing.

⬇0 ❤95 11 days ago · Uploaded Detail →
amekala amekala
from GitHub Research & Analysis
  • 📁 agents/
  • 📄 SKILL.md
ads campaigns backend

adspirer-ads

Manage ad campaigns across Google Ads, Meta Ads, LinkedIn Ads, and TikTok Ads. Use when the user wants to analyze campaign performance, research keywords, create campaigns, optimize budgets, or manage ad accounts via the Adspirer MCP server.

⬇0 ❤28 9 days ago · Uploaded Detail →
naveedharri naveedharri
from GitHub Testing & Security
  • 📄 SKILL.md
ads data microsoft

ads-audit

Full multi-platform paid advertising audit with parallel subagent delegation. Analyzes Google Ads, Meta Ads, LinkedIn Ads, TikTok Ads, and Microsoft Ads accounts. Generates health score per platform and aggregate score. Use when user says "audit", "full ad check", "analyze my ads", "account health check", or "PPC audit". --- # Full Multi-Platform Ads Audit ## Process 1. **Collect account data** — request exports, screenshots, or API access 2. **Detect business type** — analyze account signals per ads orchestrator 3. **Identify active platforms** — determine which platforms are in use 4. **Delegate to subagents** (if available, otherwise run inline sequentially): - `audit-google` — Conversion tracking, wasted spend, structure, keywords, ads, settings (G01-G74) - `audit-meta` — Pixel/CAPI health, creative fatigue, structure, audience (M01-M46) - `audit-creative` — LinkedIn, TikTok, Microsoft creative checks + cross-platform synthesis - `audit-tracking` — LinkedIn, TikTok, Microsoft tracking + cross-platform tracking health - `audit-budget` — LinkedIn, TikTok, Microsoft budget/bidding + cross-platform allocation - `audit-compliance` — All-platform compliance, settings, performance benchmarks 5. **Score** — calculate per-platform and aggregate Ads Health Score (0-100) 6. **Report** — generate prioritized action plan with Quick Wins ## Data Collection Ask the user for available data. Accept any combination: - Google Ads: account export, Change History, Search Terms Report - Meta Ads: Ads Manager export, Events Manager screenshot, EMQ scores - LinkedIn Ads: Campaign Manager export, Insight Tag status - TikTok Ads: Ads Manager export, Pixel/Events API status - Microsoft Ads: account export, UET tag status, import validation results If no exports available, audit from screenshots or manual data entry. ## Scoring Read `ads/references/scoring-system.md` for full algorithm. ### Per-Platform Weights | Platform | Category Weights | |----------|-----------------| | Google | Conve

⬇0 ❤8 11 days 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