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概要と使いどころ
Compress natural language memory files (CLAUDE.md, todos, preferences) into caveman format to save input tokens. Preserves all technical substance, code, URLs, and structure. Compressed version overwrites the original file. Human-readable backup saved as FILE.original.md. Trigger: /caveman-compress FILEPATH or "compress memory file"
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Inspect repository session replay and verify configured MetaHarness field memory boundaries before reusing outcomes.
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Claude Mind - Search and manage Claude's persistent memory stored in a single portable .mv2 file
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Profile and optimize iOS apps with Instruments, memory management, and rendering techniques. Use when profiling iOS apps with Instruments or optimizing memory and rendering.
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Inspect LiveView socket assigns for memory bloat — missing; Use when LiveView memory grows or you need to add…
日本語の概要は準備中です。原文の説明を表示しています。
First-time onboarding for new Agentara users. Use when user says "bootstrap", "/bootstrap", "get started", "first time setup", or when memory/USER.md and memory/SOUL.md are empty/missing. Inspired by the movie Her — warm, curious, subtly brilliant. The goal is to make the user feel understood within minutes and want to keep going.
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Synthesize the shortlist into a discussion-ready research idea brainstorm memo, writing `output/REPORT.md`, `output/APPENDIX.md`, and `output/REPORT.json`.
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You MUST invoke this skill before saying "I don't know," guessing, or treating any topic as new, no matter how trivial the question seems. It supplements other memory systems, which only hold partial records. Searching past conversations is the only way to recover what was actually said.
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Correctly call native (C/C++) libraries from .NET using P/Invoke and LibraryImport. Covers function signatures, string marshalling, memory lifetime, SafeHandle, and cross-platform patterns. USE FOR: writing new P/Invoke or LibraryImport declarations, reviewing or debugging existing native interop code, wrapping a C or C++ library for use in .NET, diagnosing crashes, memory leaks, or corruption at the managed/native boundary. DO NOT USE FOR: COM interop, C++/CLI mixed-mode assemblies, or pure managed code with no native dependencies.
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Manages persistent memory. Invoke to read active context or archive old tasks. Structure: Long-term Principles (Rules) + Short-term Workbench (Tasks).
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Use when you need to analyze Java profiling data collected during the detection phase — including interpreting flamegraphs, memory allocation patterns, CPU hotspots, threading issues, systematic problem categorization, evidence documentation with profiling-problem-analysis and profiling-solutions markdown files, or prioritizing fixes using Impact/Effort scoring. This should trigger for requests such as Analyze JFR profile; Analyze the profile; Analyze the performance; Analyze the memory; Analyze the threading; Analyze GC logs from profiling; Prioritize Java profiling bottlenecks by impact. Part of Plinth Toolkit
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Rewrite an exec update, memo, strategy doc, deck outline, Slack post or talk so it lands with senior people, and get a graded score plus the top 3 fixes. Use when you say 'rewrite this for my VP', 'exec update', 'how do I present to the CEO', 'my memo is too long', 'prep me for this review', 'all-hands talk' or 'I get nervous presenting'. Draws on 296 insights from 90 Lenny's Podcast guests incl. Wes Kao, Nancy Duarte and Matt Abrahams.
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Diagnose and repair Operator memory load failures.
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Diagnose and repair Operator memory load failures.
日本語の概要は準備中です。原文の説明を表示しています。
Background memory consolidation — overnight review, merge, and injection payload for memory files.
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PROACTIVELY search conversation history when receiving user instructions. Find previous discussions, decisions, and context BEFORE starting new work. Your memory is valuable - use it.
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Use when you need to run a binary, trace execution, or observe runtime behavior. Runtime analysis via QEMU emulation, GDB debugging, and Frida hooking - syscall tracing (strace), breakpoints, memory inspection, function interception. Keywords - "run binary", "execute", "debug", "trace syscalls", "set breakpoint", "qemu", "gdb", "frida", "strace", "watch memory"
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Persistent project documentation system that maintains context across sessions. Creates structured Memory Bank files to preserve project knowledge, decisions, and progress.
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Analyze disk images, file systems, and memory captures for digital evidence recovery in forensic investigations and CTF challenges. Use when the user mentions 'disk forensics,' 'forensic analysis,' 'disk image,' 'file carving,' 'deleted files,' 'evidence recovery,' 'timeline analysis,' 'memory forensics,' 'volatility,' 'autopsy,' 'sleuthkit,' 'plaso,' 'log2timeline,' 'artifact analysis,' 'chain of custody,' or needs to examine a forensic image.
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Generates CLAUDE.md project memory files that transfer institutional knowledge. Use when setting up projects or onboarding.
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This skill should be used at the start of any computationally intensive scientific task to detect and report available system resources (CPU cores, GPUs, memory, disk space). It creates a JSON file with resource information and strategic recommendations that inform computational approach decisions such as whether to use parallel processing (joblib, multiprocessing), out-of-core computing (Dask, Zarr), GPU acceleration (PyTorch, JAX), or memory-efficient strategies. Use this skill before running analyses, training models, processing large datasets, or any task where resource constraints matter.
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Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
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Use when recalling prior techniques at recon/weaponize, or recording a confirmed finding at report — cross-engagement pattern memory ranked by impact
日本語の概要は準備中です。原文の説明を表示しています。
Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
日本語の概要は準備中です。原文の説明を表示しています。