Dump PMM memory state as ASCII art in the terminal. Three depth levels: status (heatmap only), summary (heatmap + clusters + timeline), detailed (full ASCII). Runs as a subagent. Use when the user runs /pmm-dump or asks for a text-based memory overview. Trigger on: "pmm-dump", "/pmm-dump", "dump memory", "ascii memory", "text memory overview", "show memory heatmap", "memory dump", or any request for a text-based ASCII visualization of memory state. --- # PMM Dump Render PMM memory state as inline ASCII visualizations. Runs as a subagent to keep the main context clean. **Depth level:** $ARGUMENTS (default: `status` if empty or not provided) ## Invocation - `/pmm-dump` or `/pmm-dump status` — heatmap only (status level) - `/pmm-dump summary` — heatmap + cluster list + last 5 timeline entries - `/pmm-dump detailed` — full ASCII: graph map + heatmap + similarity matrix + clusters ## Behaviour Dispatch a `general-purpose` agent using the `Readonly Agent Model` from `memory/config.md` (default: `haiku`) with the prompt below. Replace `<level>` with the depth level (`status`, `summary`, or `detailed`). Replace `<project-root>` with the actual project root path. Output the agent's returned string verbatim — it contains the fully formatted ASCII visualization. ### Agent Prompt > Render PMM memory state as ASCII visualizations. This is a READ-ONLY task — do not edit any files. You may run git commands for timestamps. > > **Project root:** `<project-root>` > **Depth level:** `<level>` > > ### Depth Levels > > - `status` — Heatmap only > - `summary` — Heatmap + cluster list + last 5 timeline entries > - `detailed` — Full ASCII: graph map + heatmap + similarity matrix + clusters > > ### Visualization 1: Heatmap — File Activity (all levels) > > 1. Read `<project-root>/memory/config.md` to get the list of active files > 2. For each active file, run: `git log -1 --format="%ar|%at" -- memory/<filename>` > 3. Map the unix timestamp to a heat level: > - `████` = modified < 5 minute
Cross-platform persistent memory for coding agents. Provides session continuity, progressive retrieval, and unified memory across Claude Code, Codex, OpenCode, and Cursor.
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.
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: