skills/claude-mem-mastery/SKILL.md
Entry-point skill for using claude-mem to keep CLAUDE.md and MEMORY.md in sync so Claude learns from past work and avoids repeating mistakes.
npx skillsauth add enuno/claude-command-and-control claude-mem-coded-assistantInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This skill teaches Claude how to:
It is an entry point, not a full manual. Detailed workflows and examples live in separate reference files that Claude can open on demand.
Claude should activate this skill when:
Claude relies on:
CLAUDE.md – main project instructions.MEMORY.md – curated lessons and directions.search – index‑level observation search.timeline – temporal context around observations.get_observations – full structured details.This skill produces:
MEMORY.md – new or updated lessons, patterns, and playbooks.CLAUDE.md – refreshed rules while staying under ~1,500 tokens.High‑level behavior (details in claude-mem-usage.md):
search for recent decision, bugfix, refactor, discovery, change observations.timeline around promising IDs to see context.get_observations for a small set of high‑value IDs.MEMORY.md with:
Constraints
MEMORY.md.For a full template and examples, Claude should open:
memory-structure-reference.mdclaude-mem-usage.mdHigh‑level behavior:
Read the existing CLAUDE.md and approximate its size; keep the body around 1–1.5k tokens for optimal behavior.
Pull only current, high‑impact content from MEMORY.md:
Rewrite historical notes as timeless rules, e.g.:
Use links instead of inlining:
.clauderules/code-style.md for style..clauderules/testing.md for testing.MEMORY.md sections for deeper background.Token Discipline
Diff‑First
For concrete layouts and example diffs, Claude should open:
claude-md-layout-reference.mdexample-diffs.mdClaude must:
Always:
MEMORY.md after meaningful work with concise, actionable lessons.CLAUDE.md focused on rules that change how work is done, not on general LLM tips.Never:
CLAUDE.md or MEMORY.md entirely; always propose small diffs.Conflict resolution priority:
CLAUDE.md.MEMORY.md.Users can invoke this skill with prompts like:
“Use the claude-mem coding skill to:
- mine claude-mem for recent work,
- update MEMORY.md with lessons, and
- refresh CLAUDE.md under the ~1,500‑token budget.”
Claude should then:
search → timeline → get_observations flow.MEMORY.md with new lessons.CLAUDE.md derived from MEMORY.md.To keep this SKILL.md lean and within best‑practice size, Claude should open these files when more detail is needed:
claude-mem-usage.md – detailed claude-mem MCP workflows, filters, and example queries.memory-structure-reference.md – full MEMORY.md templates and longer examples.claude-md-layout-reference.md – canonical CLAUDE.md section layouts and size guidance.example-diffs.md – sample before/after patches for CLAUDE.md and MEMORY.md.tools
MemPalace local-first AI memory system. Use when setting up persistent memory for Claude Code sessions, mining project files or conversation transcripts, querying past context, configuring MCP tools, managing the knowledge graph, or troubleshooting palace operations.
tools
LangSmith Python SDK — trace, evaluate, and monitor LLM applications. Covers @traceable decorator, trace context manager, Client API, evaluate() / aevaluate(), comparative evaluation, custom evaluators, dataset management, prompt caching, ASGI middleware, and pytest plugin.
development
LangGraph (Python) — build stateful, controllable agent graphs with checkpointing, streaming, persistence, interrupts, fault tolerance, and durable execution. Covers both Graph API (StateGraph) and Functional API (@entrypoint/@task).
development
LangGraph Graph API (Python) — build explicit DAG agent workflows with StateGraph, typed state, nodes, edges, Command routing, Send fan-out, checkpointers, interrupts, and streaming. Use when you need explicit control flow and graph topology.