1,900 件 ・ 関連度順
概要と使いどころ
Reverses proprietary command-and-control protocols: locating send/recv routines, recovering the message framing and encryption/encoding, and reconstructing the command set to build a decoder or emulator. Activates for requests to reverse a custom C2 protocol, decode beacon traffic, or document a malware command structure.
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。
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.
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。
Reverse engineers binaries with Binary Ninja using its analysis stack and Python API to enumerate functions, navigate IL levels (LLIL/MLIL/HLIL), and automate annotation and extraction. Activates for requests to reverse a binary with Binary Ninja, script the Binary Ninja API, or work with its intermediate languages.
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。
Reverse engineers binaries using radare2/rizin interactively, covering analysis initialization, navigation, disassembly and graph views, patching, and the visual mode workflow. Activates for requests to reverse a binary with radare2 or rizin, learn r2 commands, or navigate and disassemble a sample in r2.
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。
Uses Ghidra to disassemble and decompile a binary, navigate to key routines via imports and strings, annotate decompiled code, and run headless scripts to automate extraction of C2, crypto, and config. Activates for requests to reverse engineer with Ghidra, decompile a binary, or script Ghidra headless analysis.
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。
Reverse engineers ARM/AArch64 malware by identifying the architecture and instruction set state (ARM/Thumb), parsing ELF/Mach-O ARM headers, and orienting analysis around the ARM calling convention. Activates for requests to reverse ARM binaries, analyze AArch64 malware, or handle ARM/Thumb instruction-set decoding.
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。
Malware reverse engineering and suspicious artifact analysis skill for defensive triage, static analysis, dynamic analysis planning, unpacking strategy, indicators of compromise, behavior summaries, YARA/Sigma ideas, and remediation guidance. Use for suspicious binaries, scripts, documents, logs, memory artifacts, sandbox reports, and malware family analysis in isolated environments.
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。
Detection engineering skill for writing, testing, and tuning Sigma, YARA, YARA-L, Suricata, Snort, Zeek, KQL, SPL, EQL, Chronicle, and Elastic detection rules. Covers ATT&CK coverage mapping, telemetry gap analysis, false-positive tuning, detection-as-code pipelines, and validation with Atomic Red Team and Caldera. Use to design durable detections backed by tests.
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Design and analyze engineering experiments or simulations using baseline cases, hypothesis-driven DOE, traceable data processing, defensible plots, uncertainty, and validation. Use for CFD, laboratory data, ML workflows, parameter studies, or research code.
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Analyze thermal-fluid engineering systems, experiments, CFD, and correlations with explicit assumptions, validity limits, uncertainty, and mechanism-based interpretation. Use for heat transfer, fluid mechanics, phase change, HVAC, energy systems, turbomachinery, piping, or thermal management.
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Create publication-quality, editable scientific and engineering schematics with explicit physical meaning, exact labels, visual hierarchy, and provenance. Use for experimental facilities, thermal-fluid mechanisms, workflows, graphical abstracts, system architectures, or research diagrams.
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Use when a task needs the judgment of an Environmental Engineering Technologist/Technician — verifying field meter calibration before a sampling event, computing a flow-proportional composite sampling program, checking chain-of-custody entries against 40 CFR 136 holding times, running an air-monitoring isokinetic sampling check, or deciding whether a field QC exception invalidates a sample.
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。
Use when a task needs the judgment of an Engineering Teacher, Postsecondary — diagnosing a spike in a gatekeeper course's D/F/W rate, running a capstone design course with an industry sponsor, closing the loop on an ABET student-outcome assessment, or building a tenure/promotion teaching-effectiveness case beyond raw student evaluation scores.
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。
Use when a task needs the judgment of an Electrical and Electronic Engineering Technologist/Technician — bench-testing a prototype board against a power or timing spec, isolating a resistive fault in a power path with node-to-node voltage-drop measurements, checking whether an oscilloscope's own bandwidth is limiting a rise-time measurement before trusting it, running a power-supply load-regulation sweep, or evaluating ESD-event provenance and IPC-A-610 acceptance on a returned unit.
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。
Use when a task needs the judgment of a Civil Engineering Technician — running and interpreting a concrete field acceptance test (slump, air content, cylinder breaks against ACI 318 criteria), verifying soil compaction against a Proctor density curve, reconciling a concrete or rebar quantity takeoff against a pay application, or documenting a field condition that deviates from the approved plans for the engineer of record.
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Use when a task needs the judgment of a Chief Technology Officer — deciding build vs buy for a core system, choosing whether an architecture bet is worth a full rewrite, sizing an SLA/uptime commitment against engineering cost, structuring engineering teams around a product roadmap, or writing the technical risk section of a board update.
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。
Use when a task needs the judgment of a biomedical/bioengineering engineer — running a design control phase (inputs, outputs, verification, validation) for a medical device, scoring a Design FMEA and deciding whether a failure mode needs mitigation, planning a human factors/usability validation study, building a design traceability matrix, or writing a design verification or risk-mitigation report. Distinct from a regulatory-affairs-specialist (owns the submission/clearance process, not the engineering itself) and from a clinical-data-manager/biostatistician (trial data and analysis, not device design).
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Use when a task needs the judgment of an Aerospace Engineering and Operations Technologist/Technician — verifying an installed fastener's preload against a drawing's torque callout via the T=K·D·F relationship, reducing strain-gauge data from a structural proof-load test into stress and checking it against an FEA-predicted margin, selecting and executing an NDI method against a defect type and material, reducing a wind-tunnel test point's dynamic-pressure and Reynolds-number data, or ballooning and dispositioning an AS9102 first article inspection. Distinct from an aerospace-engineer (owns the design, structural analysis, and certification basis) — this role builds, instruments, tests, and inspects the hardware the engineer specified, closing the loop with measurement rather than deriving a new analysis.
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Use when a task needs the judgment of an Architecture/Engineering firm or department manager — pricing a project fee (lump sum vs. hourly vs. % of construction cost), staffing a project against backlog, evaluating scope creep on a fixed-fee job, managing professional liability exposure, or deciding whether to pursue a project given current utilization.
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Decompose large epics into sprint-ready sub-epics using 9 splitting patterns. Use this skill when: - A spec is approved and you need to break a large feature into estimable work items for engineering - You want to split an epic that is too large for a single sprint - You need sized sub-epics with story point estimates for sprint planning - You are preparing for engineering handoff and need to identify work packages
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Write a concise feature spec for engineering handoff. Use when the user says "write a spec", "feature spec", "one-pager for eng", "spec this out", "write up this feature", "I need to hand this off to engineering", "shape this up", or wants a concise technical brief - even if they don't say "feature spec".
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。
Write a component spec for engineering handoff. Use when the user says "component spec", "design handoff", "spec this component", "document this component for engineering", "Figma handoff", "component documentation", "how do I hand this off", or needs to communicate a UI component design to developers - even if they don't explicitly say "component spec".
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。
Design and implement features from raw data for machine learning models. Use when the user says "engineer features", "feature engineering for X", "create features from this dataset", "transform these variables", "encode categoricals", "handle skew", "create interaction features", "lag features", "extract features from text or dates", "improve model performance with better features", or wants to move from raw columns to model-ready inputs.
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。
Universal prompt engineering techniques for any LLM. Use when crafting, optimizing, or reviewing prompts for AI models. Triggers on requests like "improve this prompt", "write a system prompt", "optimize my instructions", "help me prompt engineer", "audit this prompt", "review my prompt", or when building agentic systems that need structured prompts.
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。