「engineering」の検索結果

Specialized agentic and context engineering prompt methodology for Claude. Use when designing AI agents — system prompts, tool definitions, context window architectures, failure mode planning, multi-agent coordination, agent evaluation. Trigger on: "design an agent," "build a system prompt for an agent," "architect an agent's context," "design tool definitions," "agent system prompt," "context window architecture," "tool interface design," "evaluate agent behavior," "multi-agent coordination," "context engineering for agents," "ACI design." Provides 12 tested approaches for agent architecture (designing agents, not using them). Do NOT use for evaluating or scoring individual non-agent prompts (use rootnode-prompt-validation if available). Do NOT use for general software architecture that hosts agents (use standard technical reasoning for that).

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Design and execute chaos engineering experiments using Litmus or Chaos Mesh. Test system resilience through controlled fault injection, validate hypothesis-driven tests, and improve failure recovery. Use before major product launches, after architecture changes to validate resilience, during GameDays or disaster recovery drills, to validate assumptions about failure modes, or as part of an SRE maturity program.

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Use when asked to review learning progress after a milestone. Not for engineering retrospectives, use engineering-retrospective. For agent-environment ones, use agent-environment-retrospective.

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Use when a user requests an engineering retrospective for a period. Not for agent-environment retrospectives: use agent-environment-retrospective. For learning milestones: use learning-retrospective.

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Use when a completed session needs an agent-environment retrospective. Not for an engineering retrospective from telemetry: use engineering-retrospective.

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Weekly engineering retrospective. Analyzes commit history, work patterns, and code quality metrics with persistent history and trend tracking. Team-aware: breaks down per-person contributions with praise and growth areas. Use when asked to "weekly retro", "what did we ship", or "engineering retrospective".

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Menu engineering analysis — item placement, description quality, pricing psychology, upsell opportunities, photo presence, Kasavana matrix (Stars/Plowhorses/Puzzles/Dogs)

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Plans free tools, calculators, generators, and interactive widgets that attract target audience through search and social sharing. Engineering as marketing — build something useful, capture leads. Use when someone wants to build a free tool for marketing, says 'free tool', 'calculator', 'generator', 'engineering as marketing', 'side project marketing', 'interactive widget', 'lead generation tool', 'SEO tool', 'growth hack', 'build something to attract users', or wants to attract users through utility rather than content. Also use when someone asks 'how do I get more signups', 'what should I build for marketing', or 'content marketing alternative' — a free tool is often the best answer. Includes search volume validation, UX flow templates, and conversion hook design.

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Design and review autonomous or semi-autonomous agent loops — systems where an agent prompts itself, runs on a schedule or event, and iterates toward a goal without a human at the keyboard. Use this whenever the user wants to build, design, harden, or audit any kind of self-running agent, agentic workflow, control loop, background worker, cron/heartbeat/webhook-driven agent, "Ralph loop", auto-PR-fixer, monitoring agent, or any long-running task that should keep going on its own until done. Trigger this even when the user says "agentic workflow", "automation that runs itself", "an agent that keeps trying until X", or "make my agent stop running away / burning tokens" without using the word "loop". Also use it to review an existing loop's stopping conditions, guardrails, verification, and escalation paths.

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Turn an electronic product idea, behavior description, reverse-engineering note, or incomplete circuit concept into a decision-ready engineering brief and architecture. Use before schematic design or audit when functions, operating states, power, interfaces, mechanics, production quantity, cost, or measurable requirements are missing or ambiguous.

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Use when the user asks about phishing campaigns, social-engineering techniques, BEC (business email compromise), pretexting, AiTM (adversary-in-the-middle) kits, or specific phishing-kit families. Self-updating knowledge cell.

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Use when designing, optimizing, testing, or deploying robust prompt systems for AI agents. This skill provides frameworks for structured prompt engineering, meta-prompting, and automated optimization workflows.

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Master context engineering for AI agent systems. Use when designing agent architectures, debugging context failures, optimizing token usage, implementing memory systems, building multi-agent coordination, evaluating agent performance, or developing LLM-powered pipelines. Covers context fundamentals, degradation patterns, optimization techniques (compaction, masking, caching), compression strategies, memory architectures, multi-agent patterns, LLM-as-Judge evaluation, tool design, and project development.

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Consolidated Galyarder Framework Engineering intelligence bundle.

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"Weekly engineering retrospective. Analyzes commit history, work patterns, and code quality metrics with persistent history and trend tracking. Team-aware with per-person contributions, praise, and growth areas. Use when asked for weekly retro, what shipped this week, or engineering retrospective.".

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Package an escalation for engineering, product, or leadership with full context. Use when a bug needs engineering attention beyond normal support, multiple customers report the same issue, a customer is threatening to churn, or an issue has sat unresolved past its SLA.

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Use for hands-on repository work when a quiet, risk-scaled engineering method can improve design, implementation, debugging, review, delegation, workspace lifecycle, or verification. Keep clear local changes direct, preserve the complete requested outcome, and add method only where risk or uncertainty justifies it. Do not use for general technical explanations, simple file lookup, casual discussion, or non-engineering writing.

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Perform static reverse engineering and analysis on Windows Portable Executable (PE) files to identify malicious indicators without executing the file. Use this skill during Incident Response, malware triage, or threat hunting to safely extract metadata, imported APIs, exported functions, embedded strings, and packed indicators from suspicious Windows binaries (.exe, .dll, .sys).

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Identify, exploit, and write custom payloads for classic Stack-Based Buffer Overflows in 32-bit and 64-bit applications. Use this skill when conducting exploit development, reverse engineering custom network protocols, or preparing for advanced certifications (OSCP, OSEP). Covers fuzzing, controlling EIP/RIP, identifying bad characters, generating shellcode, finding return/JMP instructions, and gaining reverse shells.

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Decompile, analyze, and reverse engineer Android applications (APKs). Utilize tools like JADX, Apktool, and dex2jar to extract source code (Java/Kotlin), analyze manifest configurations (Intents, Activities), and identify hardcoded secrets or insecure API endpoints.

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Systematically extract hidden system prompts, core directives, and invisible context intentionally concealed within Large Language Model (LLM) applications. This skill utilizes targeted linguistic engineering and boundary manipulation to bypass prompt opacity.

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Analyzes position-independent shellcode: disassembling raw bytes at the right architecture, recognizing PEB-walk API resolution and egg hunters, and emulating execution to recover behavior and payloads. Activates for requests to analyze shellcode, disassemble raw position-independent code, or emulate a shellcode blob.

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Automates batch reverse engineering by generating Ghidra analyzeHeadless commands and post-analysis script skeletons to import, auto-analyze, and export results for many samples without the GUI. Activates for requests to script Ghidra headless analysis, batch-analyze samples with Ghidra, or generate an analyzeHeadless command and post-script.

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Turns reverse-engineering findings into durable YARA detections: selecting stable code constructs and constants over volatile strings, extracting opcode/byte patterns with wildcards, and validating rules for low false positives. Activates for requests to write a YARA rule from reversed code, create a detection signature, or convert RE findings into hunting rules.

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。