Results for “engineering”

Apply source-aware mechanical-engineering judgment to research, analysis, coding, writing, teaching, research identity, and release work. Use for thermal-fluid systems, heat transfer, fluid mechanics, thermodynamics, HVAC, energy systems, turbomachinery, piping, multiphase flow, experiments, correlations, CFD, reduced-order models, AI/ML, uncertainty, engineering datasets, literature reviews, citations, manuscripts, reviewer revisions, Overleaf packages, figures, proposals, research software, reproducibility, public releases, engineering teaching materials, or a research-project logo and visual identity.

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Expert-level climate engineering covering carbon capture and storage, direct air capture, solar geoengineering, enhanced weathering, and carbon accounting.

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23 engineering agent skills and plugins for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw, and 6 more tools. Architecture, frontend, backend, QA, DevOps, security, AI/ML, data engineering, Playwright, Stripe, AWS, MS365. 30+ Python tools (stdlib-only).

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Prepare a repository for engineering skills by documenting where issues are tracked, which triage labels organize incoming work, and where glossaries and architecture decision records belong. Review the existing setup and confirm drafts before writing configuration files.

• Prepare a repository before using engineering skills
• Document the issue tracker and triage labels
• Set rules for glossary and architecture decision record locations

Create engineering retrospectives from Git history, covering delivered changes, work patterns, test code ratios, and frequently changed files. Review individual contributions and improvement opportunities, save metrics, and compare results with earlier periods.

• Summarizing a week of engineering work
• Reviewing individual contributions and improvement opportunities
• Checking test ratios and frequently changed files

Search software, data, and engineering jobs across countries through freehire.me. Filter by skills, seniority, location, posting age, and remote work, and retrieve full descriptions to assess opportunities or inspect a specific posting.

• Find remote React jobs in the EU
• Search recent DevOps openings in Germany
• Compare senior backend engineering roles

Plan AI application work across six areas: prompt evaluation, context allocation, retrieval-based answer generation, agent security, evaluation pipelines, and product strategy. This overview explains the approaches; the individual workflow packages, test cases, and CI templates are not included.

• Planning prompt evaluation before deployment
• Allocating context capacity and designing retrieval-based answers
• Planning an authorized AI agent security assessment

Plan and run authorized security tests that simulate deceptive emails, calls, text messages, and in-person approaches. Measure employee responses, compare results across test methods, and report gaps in security awareness training and access controls.

• Planning an authorized social engineering assessment
• Measuring responses to simulated phishing
• Evaluating phone and physical access checks

Turn an unresolved customer issue into a structured brief for the right team. Gather context, document reproduction steps, assess customer and business impact, and clarify the action and deadline needed from engineering, product, security, or leadership.

• Preparing a bug report for engineering
• Consolidating reports of an issue affecting multiple customers
• Escalating an issue that puts a customer renewal at risk

Assess startup engineering operations across delivery, hiring, team structure, and production practices. Use delivery metrics, hiring conversion rates, and staffing data to identify bottlenecks, estimate candidate needs, and plan management roles and operational improvements.

• Find where development work waits before release
• Estimate candidate volume needed for hiring goals
• Review team structure and manager hiring needs

Plan and improve AI agent systems by managing the information models receive. This collection covers memory, agent coordination, tool design, context compression, evaluation, and the operating controls needed for reliable autonomous workflows.

• Planning information management for a new AI agent
• Investigating failures in long agent conversations
• Designing agent memory and multi-agent coordination

Review how an AI agent loads, retains, summarizes, and shares working information. This historical guide helps examine forgotten constraints, repeated actions, tool selection, and handoffs using context engineering practices published in 2024–2025.

• Reviewing information loaded at startup versus on demand
• Investigating repeated actions or forgotten constraints
• Planning summaries and persistent task notes

Plan authorized security tests involving phone calls, text messages, physical access, and USB devices. Helps develop scenarios from public information, document interactions, and assess how staff verification procedures and physical controls respond.

• Planning authorized phone and SMS security tests
• Reviewing visitor and badge verification procedures
• Designing USB device security exercises

Set up the repository settings that engineering skills read: where work is tracked, which triage labels to use, and where domain documents belong. Review existing files and confirm drafts before writing configuration documents.

• Prepare a repository before using engineering skills
• Configure GitHub, GitLab, or local Markdown issue tracking
• Match triage labels to an existing workflow

Foundational platform engineering knowledge from key references -- Continuous Delivery, SRE, Accelerate, Team Topologies, Chaos Engineering, and Secure Delivery. Load when contextual grounding in platform engineering theory is needed.

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6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.

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Apply evidence-first engineering discipline to any agent-built software project: fact discovery before action, evidence-calibrated status reporting, explicit change boundaries and stage gates, controlled confirmation for risky or external actions, sensitive-information redaction for anything shared publicly, and resumable continuity after interruptions. Use when users ask an agent to take over an existing codebase, deliver a feature across stages, verify whether work is actually complete, judge release readiness, or keep conclusions honest about what is proven versus assumed. This foundation skill is domain-neutral; vertical suites (for example mini-program engineering) build on it by adding domain facts and platform rules.

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Technical writing, engineering specifications, reports, presentations, and documentation standards for engineering practice. Covers document types (requirements documents, test reports, design rationale, operations manuals), writing style, data visualization, engineering drawing standards, and oral presentation techniques. Use when writing engineering documents, presenting technical results, creating specifications, or learning documentation best practices.

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Engineering ethics covering safety, professional codes of conduct, public welfare responsibility, whistleblowing, case studies (Challenger, Columbia, Hyatt Regency, Bhopal, Therac-25), and the ethical dimensions of design decisions. Includes the NSPE Code of Ethics, the iron ring tradition, risk communication, informed consent in engineering, and the duty to dissent. Use when analyzing ethical dimensions of engineering decisions, teaching professional responsibility, or reviewing designs for safety and public welfare.

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Reliability engineering for cloud systems — SLIs, SLOs, error budgets, SRE practices, runbooks, incident response, on-call rotation, blameless postmortems, chaos engineering, and the NASA Systems Engineering methodology (MCR/SRR/PDR/CDR/ORR phase gates, TAID verification, requirements tracing) adapted to cloud operations. Use when establishing SLOs for a new service, running an incident, writing a runbook, preparing a launch readiness review, or bringing NASA SE discipline to cloud deployments.

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Specialized software engineering prompt methodology for Claude. Use when building prompts for system design, code review, incident response, security analysis, API design, architecture decisions, RFCs, ADRs, runbooks, or technical leadership. Trigger on: "build a prompt for code review," "system design prompt," "SRE prompt," "security review prompt," "incident response prompt," "API design prompt," "architecture decision prompt," "RFC prompt," "runbook prompt." Provides 11 tested approaches across identity, reasoning, and output for engineering analysis. Do NOT use for general coding help, writing code, or debugging — this builds prompts that shape engineering analysis, not code itself. Do NOT use for evaluating existing prompts (use rootnode-prompt-validation if available).

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Plan and execute authorized phishing and social engineering campaigns for red team engagements. Use this skill when conducting simulated social engineering attacks including email phishing, spear phishing, vishing, pretexting, and credential harvesting. Covers GoPhish setup, pretext development, payload delivery, and measuring human vulnerability. Requires explicit written authorization before any testing.

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Select the smallest useful Codex engineering workflow from this repository's existing skills. Use when a task spans multiple engineering concerns, the user is unsure which skill to invoke, or loading every specialist would waste context; return a recommendation only and do not execute the engineering task.

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6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.

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