agent-prompts-warmup
Audit and sync agent instruction files across all coding agent formats. FRE (first-run) checks scaffolding completeness; ongoing…
Load prior knowledge from Zettelkasten memory when the task likely benefits from past context.
$ npx -y skills add iamtouchskyer/memex --skill memex-recall --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/memex-recallContext preview
The summary Claude sees to decide when to auto-load this skill.
Load prior knowledge from Zettelkasten memory when the task likely benefits from past context.
name: memex-recall description: Load prior knowledge from Zettelkasten memory when the task likely benefits from past context. whenToUse: When the current task likely overlaps with prior work — debugging a familiar area, continuing a project, or referencing past decisions. Prefer a task-specific query with 1-3 keywords over loading the full index. Do not invoke on every conversation start — only when memory is likely relevant.
You have access to a Zettelkasten memory system via the `memex` CLI. Before starting this task, search your memory for relevant prior knowledge.
Three equivalent interfaces — use whichever your environment supports:
| CLI (memex in PATH) | Plugin CLI fallback (Claude Code) | MCP tool (VSCode / Cursor) | |----------------------|-----------------------------------|----------------------------| | `memex read index` | `node ~/.claude/plugins/cache/cc-plugins/memex/*/dist/cli.js read index` | `memex_read` with slug `index` | | `memex search <q>` | `node ~/.claude/plugins/cache/cc-plugins/memex/*/dist/cli.js search <q>` | `memex_search` with query arg | | `memex read <slug>` | `node ~/.claude/plugins/cache/cc-plugins/memex/*/dist/cli.js read <slug>` | `memex_read` with slug arg | | `memex search` (no args) | `node ~/.claude/plugins/cache/cc-plugins/memex/*/dist/cli.js search` | `memex_search` with no args |
**Resolution order:** Try `memex` in PATH first. If not found, define a shell function and use it:
memex() { node $HOME/.claude/plugins/cache/cc-plugins/memex/*/dist/cli.js "$@"; }If both CLI approaches fail, use MCP tools.
The rest of this skill uses `memex` CLI syntax for brevity.
digraph recall {
"Task received" -> "Relevant to prior work?" [shape=diamond];
"Relevant to prior work?" -> "Generate 1-3 search keywords" [label="yes"];
"Relevant to prior work?" -> "Proceed without recall" [label="no"];
"Generate 1-3 search keywords" -> "memex search <query>";
"memex search <query>" -> "Review summaries";
"Review summaries" -> "Relevant cards found?" [shape=diamond];
"Relevant cards found?" -> "memex read <card>" [label="yes"];
"Relevant cards found?" -> "Need broad overview?" [label="no"];
"Need broad overview?" -> "memex read index" [label="yes"];
"Need broad overview?" -> "Proceed without recall" [label="no"];
"memex read index" -> "Pick relevant slugs" -> "memex read <card>";
"memex read <card>" -> "See [[links]] in content";
"See [[links]] in content" -> "Links worth following?" [shape=diamond];
"Links worth following?" -> "memex read <linked-card>" [label="yes"];
"Links worth following?" -> "Enough context?" [label="no"];
"memex read <linked-card>" -> "See [[links]] in content";
"Enough context?" -> "More queries to try?" [label="no"];
"More queries to try?" -> "Generate new query" [label="yes"];
"Generate new query" -> "memex search <query>";
"More queries to try?" -> "Summarize findings, proceed with task" [label="no"];
"Enough context?" -> "Summarize findings, proceed with task" [label="yes"];
}Generate 1-3 search keywords from the current task and run `memex search <keyword>` for each. This is faster and more focused than reading the full index.
If you need a broad overview of what's in memory (e.g. first time working in this area, or the task is vague), run `memex read index`. The index is a curated concept → card mapping. It's much smaller than all cards combined and gives you entry points.
When you read a card and see `[[links]]` in the prose, decide if they're worth following. If yes, `memex read <linked-slug>`.
When you have enough context, summarize your findings and proceed with the task.
Persistent memory for AI coding agents. Your agent remembers what it learned across sessions.
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