「engineer」の検索結果

Maintain a review-first Markdown knowledge base for Codex practices with source provenance, engineering capture, citation-aware queries, explicit archive and promotion, and deterministic linting. Use when asked to capture a durable engineering lesson, ingest Codex research, query or archive what the repository knows, check wiki health, reconcile conflicting guidance, or promote verified knowledge.

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Coordinate complex engineering work across bounded subagents while protecting the main context, preventing edit conflicts, and measuring whether delegation was worthwhile. Use when the user asks to delegate, parallelize, orchestrate, use subagents, fan out a review, or handle a large task with independent workstreams; do not use for small, tightly coupled, or inherently sequential tasks.

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 engineer and security-test Telegram bots — API analysis, callback interception, exploit discovery, and vulnerability documentation

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。

Shared support references for the rolling-wave engineering skill set. Use only when a rolling-wave workflow skill explicitly points here, or when maintaining the shape-project, prepare-next-slice, implement-slice, finalize-slice, and complete-slice skills.

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Shape or update a rolling-wave engineering project before slice preparation. Use when the user wants to start a rolling-wave project, define the finish line, clarify success criteria, create or update docs/rolling-wave/{project}/project.md, sketch a broad roadmap, or interrogate project-level direction without implementation details.

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。

Expert-level transportation engineering covering highway design, traffic flow, intersection design, pavement design, traffic impact studies, and public transit.

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Expert-level nanomaterials engineering covering synthesis, characterization, properties at nanoscale, nanocomposites, safety, and industrial applications of nanomaterials.

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Expert-level geotechnical engineering covering soil classification, shear strength, consolidation, foundation design, slope stability, and retaining structures.

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Configure this repo for the engineering skills — set up its issue tracker, triage label vocabulary, and domain doc layout. Run once before first use of the other engineering skills.

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。

QA engineer for test automation and coverage. Use when the user asks to talk to Quinn or requests the QA engineer.

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。

Construa sistemas de ML em produção com PyTorch 2.x, TensorFlow e frameworks modernos de ML. Implementa model serving, feature engineering, A/B testing e monitoramento.

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。

Configure this repo for the engineering skills — set up its issue tracker, triage label vocabulary, and domain doc layout. Run once before first use of the other engineering skills.

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 phishing and social engineering simulations with explicit authorization and measurable outcomes.

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。

QA Engineer role in AID methodology. Use for test strategy, BDD scenarios, bug reporting, acceptance testing, flaky test prevention.

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。

Master Anthropic's prompt engineering techniques to generate new prompts or improve existing ones using best practices for Claude AI models.

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。

Engineering operating model for teams where AI agents generate a large share of implementation output.

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Spearphishing simulation is a targeted social engineering attack vector used by red teams to gain initial access. Unlike broad phishing campaigns, spearphishing uses OSINT-derived intelligence to craf

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Extract and catalog attack patterns from cyber threat intelligence reports into a structured STIX-based library mapped to MITRE ATT&CK for detection engineering and threat-informed defense.

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 engineer Go-compiled malware using Ghidra with specialized scripts for function recovery, string extraction, and type reconstruction in stripped Go binaries.

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Analyzes malicious Linux ELF (Executable and Linkable Format) binaries including botnets, cryptominers, ransomware, and rootkits targeting Linux servers, containers, and cloud infrastructure. Covers static analysis, dynamic tracing, and reverse engineering of x86_64 and ARM ELF samples. Activates for requests involving Linux malware analysis, ELF binary investigation, Linux server compromise assessment, or container malware analysis.

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Use when designing, evaluating, documenting, modernizing, reviewing, refactoring, or implementing software architecture and code-level structure, including requirements, context, architecture style selection, microservices patterns, WebAssembly/WASI/Component Model, UMA portable capabilities, runtime contracts, capability graphs, governed MCP/agent orchestration, clean code, code smells, Rust crate/library API architecture, Cargo feature/MSRV/SemVer policy, unsafe/FFI/no_std/library testing, modularity, views, NFR tactics, IAM/auth, security patterns, cost estimation, architecture-as-code fitness functions, ADR/RFC work, and engineering execution plans.

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Product-discovery coach for Fishbowl engineers — inspired by Marty Cagan's work (never impersonates him). Stage-routes between opportunity brief, research, PRD, ticket drafting, and outcome review. Triggers on "product coach", "help me with product", "I need to write a PRD", "I want to do discovery", "opportunity assessment", "who is this for", "why are we building this", or when an engineer is starting, resuming, or post-mortem-ing product-adjacent work. Invoke with a short description of what you want to do, or invoke bare to be surveyed and routed.

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Knowledge base from the NASA Systems Modeling Handbook for Systems Engineering (NASA-HDBK-1009A Rev A, 2025). Use for model-based systems engineering (MBSE) wired into NASA's NPR 7123.1 SE processes: the three aspects of MBSE (language / methodology / framework), the NASA SE Engine and its two OOSEM-derived steps (Model Planning, Setting Up the Model), the Modeling Plan as a SEMP subset, the tool-agnostic NASA SE metamodel of elements and relationships across the four SysML pillars (structure / behavior / requirements / parametrics), worked SysML diagrams and tables for stakeholders, requirements, structure and V&V, generating SE work products (ConOps, MOE, MOP, TPM, V&V), the MBSE Grid framework, alternative modeling approaches (PBR, Scenario, System Specification, Verification), and the ConOps model-content template. Scope is bounded to four common technical processes (Stakeholder Expectation Definition, Technical Requirements Definition, Product Verification, Product Validation). Does NOT teach SysML itself, mandate a tool, define NPR 7123.1 processes, cover technical-management processes 10-17, or reproduce the OMG SysML specification.

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Knowledge base from the OUSD(R&E) guidebook Implementing a MOSA in DoD Programs (Feb 2025). Use for the Modular Open Systems Approach as a DoD acquisition + design discipline: the statutory/regulatory basis (10 U.S.C. 4401–4403, FY2017/FY2021 NDAA, DFARS), the five OUSD(R&E) pillars, the plan→modularize→identify→define→standardize interface lifecycle, technical levers (WBS/MIL-STD-881F taxonomy, standards profiling, API-first software, COTS/cybersecurity), MOSA assessment metrics and tools (PART/OAAT/KOSS/SEAM/MAUT), technology-change and DMSMS management, roadmaps, MOSA across the six AAF pathways, and contracting/IP/data-rights mechanics. SCOPE LIMITS: this is U.S. DoD weapon-system acquisition policy, not a general open-architecture or interface-standards reference — it names standards (FACE, OMS, DISR) without reproducing them, is light on detailed engineering of any specific standard, and does not cover the underlying SE processes (use dau-se-guidebook / nasa-npr-7123) or general systems-engineering theory (use sebok).

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。