backend
De la autor
Backend engineering judgment, distilled from a stronger model - invoke when CHOOSING a tech stack, language, database, queue, or architecture; designing a service, API, business logic, or schema; making a system production-ready (observability, failure handling, security); or reviewing server-side code and judging codebase health. Scenario-driven stack tradeoffs, logic-design rules, data discipline, production floors, and a rot catalog (the early signs of unmaintainable code).
Instalare
npx skills add telagod/code-abyss --skill backend -a claude-code
Se instalează în .claude/skills/backend/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
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Verificări de siguranță pe SKILL.md
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De ce 80
aiqbench calculează scorul de încredere din semnale publice. Nu este un audit de securitate, așa că citește un skill înainte să-l instalezi.
Skill-uri similare
Cele mai apropiate de acesta prin ce fac și când sunt folosite.
- backend-developmentMoizIbnYousaf/ai-agent-skillsBackend API design, database architecture, microservices patterns, and test-driven development. Use for designing APIs, database schemas, or backend system architecture.Testare★ 1.2K
- securitytelagod/code-abyssDefensive security engineering judgment, distilled from a stronger model - invoke when THREAT MODELING a system or feature; making security-relevant design decisions (auth, crypto, trust boundaries, attack surface); reviewing code for vulnerabilities (injection, IDOR, secrets, the OWASP classes); hardening operations (secrets management, detection, patching, incident response); or judging whether a security control/program is real or theater. Also invoke BEFORE any offensive-flavored request (pentest, exploit, credential testing) to apply the authorization gate. Also invoke when designing, reviewing, or hardening an LLM/agent system that reads untrusted content or holds tool/MCP access (prompt injection, excessive agency, MCP supply chain).Securitate★ 242
- hardwaretelagod/code-abyssElectronics and embedded engineering judgment, distilled from a stronger model - invoke when CHOOSING components, MCUs, modules, or interfaces; designing or reviewing a circuit, power tree, or PCB; writing embedded firmware; debugging physical hardware (resets, noise, dead boards, flaky sensors); or planning bring-up and validation of a new board. Scenario-driven part selection, electrical design margins, firmware-for-unattended-devices rules, bench debugging discipline, and a trap catalog.Design★ 242
- ai-development-guideshinpr/claude-code-workflowsApplies language-agnostic and backend technical decision criteria, anti-pattern detection, debugging, and quality gates. Use when reviewing general/backend implementation choices, code smells, failures, or implementation completeness.Inginerie★ 704
- frontendtelagod/code-abyssVisual design taste for web UI, distilled from a stronger model's aesthetic - invoke when about to BUILD or STYLE any web page, component, artifact, or UI; picking a visual direction; writing CSS; reviewing how a design looks; or when a design works but feels generic or boring. Named style directions with exact tokens, concrete craft numbers, and a catalog of garbage design to refuse.Design★ 242
- mltelagod/code-abyssMachine learning and LLM engineering judgment, distilled from a stronger model - invoke when DECIDING whether/how to use ML or an LLM for a task (prompt vs RAG vs fine-tune vs classical); working with training/eval data or labels; building or reviewing evals for models and LLM features; designing RAG, structured output, or agent pipelines; or diagnosing why a model/LLM feature underperforms. Method-selection ladder, data and leakage discipline, eval-as-spec rules, LLM-era craft, and a trap catalog.Planificare★ 242
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