Persistent memory enhancement for AI agents. Store conversations, search memories with semantic retrieval, and recall context across sessions. Use this skill when you need to remember user preferences, past conversations, project context, or any information that should persist beyond the current session. Provides tiered access (abstract/overview/content) for efficient context management.
Ingest Claude Code conversation history into the Obsidian wiki. Use this skill when the user wants to mine their past Claude conversations for knowledge, import their ~/.claude folder, extract insights from previous coding sessions, or says things like "process my Claude history", "add my conversations to the wiki", "what have I discussed with Claude before". Also triggers when the user mentions their .claude folder, Claude projects, session data, or past conversation logs. --- # Claude History Ingest — Conversation Mining You are extracting knowledge from the user's past Claude Code conversations and distilling it into the Obsidian wiki. Conversations are rich but messy — your job is to find the signal and compile it. ## Before You Start 1. Read `.env` to get `OBSIDIAN_VAULT_PATH` and `CLAUDE_HISTORY_PATH` (defaults to `~/.claude`) 2. Read `.manifest.json` at the vault root to check what's already been ingested 3. Read `index.md` at the vault root to know what the wiki already contains ## Ingest Modes ### Append Mode (default) Check `.manifest.json` for each source file (conversation JSONL, memory file). Only process: - Files not in the manifest (new conversations, new memory files, new projects) - Files whose modification time is newer than their `ingested_at` in the manifest This is usually what you want — the user ran a few new sessions and wants to capture the delta. ### Full Mode Process everything regardless of manifest. Use after a `wiki-rebuild` or if the user explicitly asks. ## Claude Code Data Layout Claude Code stores everything under `~/.claude/`. Here is the actual structure: ``` ~/.claude/ ├── projects/ # Per-project directories │ ├── -Users-name-project-a/ # Path-derived name (slashes → dashes) │ │ ├── <session-uuid>.jsonl # Conversation data (JSONL) │ │ └── memory/ # Structured memories │ │ ├── MEMORY.md # Memory index │ │ ├── user_*.md # U
Long-term memory service for LLM agents. Provides persistent, structured memory (Cognitive Nexus) through three operations: Formation (encode conversations into memory), Recall (query memory with natural language), and Maintenance (consolidate and prune memory).
This skill should be used when the user asks to 'evolve CLAUDE.md', 'update CLAUDE.md from experience', or 'self-evolve'. Scans conversations and notes to extract actionable findings and appends them to CLAUDE.md.
You have access to GoHighLevel (GHL) CRM data through the MCP integration. Use this skill to manage contacts, conversations, opportunities, and monitor business metrics across insurance agency sub-accounts.
Build AI chat interfaces using ai-elements components — conversations, messages, tool displays, prompt inputs, and more. Use when the user wants to build a chatbot, AI assistant UI, or any AI-powered chat interface.
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:
