Configures Claude Code hooks and Codex hooks.json/notify callbacks. Use when adding guardrails, preflight, audit trails, worktree automation, or budget enforcement.
Quellsprache: Englisch
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SkillsMP hat 140 Skills aus vasilyu1983/AI-Agents-public gesammelt. Öffne einen Skill, um Quelle und Details zu prüfen.
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Configures Claude Code hooks and Codex hooks.json/notify callbacks. Use when adding guardrails, preflight, audit trails, worktree automation, or budget enforcement.
Quellsprache: Englisch
Configures and hardens MCP servers for Claude Code and Codex agents. Use when connecting databases, APIs, files, or SaaS via MCP, or building custom servers.
Quellsprache: Englisch
Manages AGENTS.md, CLAUDE.md, and scoped repo rules for Claude Code and Codex. Use when fixing stale memory, ignored instructions, memory audits, or model-upgrade migration.
Quellsprache: Englisch
Adds per-skill learnings loops for dated patterns, mistakes, and domain facts. Use when wiring skill memory, consolidation, or drift audits.
Quellsprache: Englisch
Creates and audits agent skills with SKILL.md, references, scripts, and platform-scoped metadata. Use when creating, updating, or validating shared skills.
Quellsprache: Englisch
Coordinates multi-agent execution across subagents, teams, and workflows. Use when planning dependency-aware fan-out, verifier passes, runtime selection, or Loop Engineering.
Quellsprache: Englisch
AI agent architecture, graph and loop composition, protocol choice, evaluation, and observability. Use when scoping or reviewing systems before implementation.
Quellsprache: Englisch
Designs execution sandboxes for coding agents. Use when modeling process isolation, filesystem policy, network controls, workspace mounts, or destructive-command boundaries.
Quellsprache: Englisch
Designs coding-agent observability and evals. Use when measuring traces, replay, checkpoint lineage, quality trajectories, tool grading, regression, or cost.
Quellsprache: Englisch
Designs approval and permission systems for coding-agent runtimes. Use when modeling tool approvals, plan-mode transitions, sandbox prompts, or worker permission handoffs.
Quellsprache: Englisch
Creates coding agents on Claude Code, Codex, and Agent SDK. Use when defining review, test, refactor, or team agents — not building a runtime.
Quellsprache: Englisch
Designs task runtimes for Loop Engineering, Graph Engineering, and background work. Use when work needs task lists, cyclic/workflow graphs, cancellation, or teammate coordination.
Quellsprache: Englisch
Designs trustworthy LLM/agent evals and optimization loops. Use when building graders, calibrating judges, choosing eval/fine-tune methods, thresholds, or fixing noisy scores.
Quellsprache: Englisch
Guides the LLM lifecycle from strategy to deployment. Use when planning, comparing, fine-tuning, distilling, compressing, migrating, or operating LLM systems.
Quellsprache: Englisch
Prompt engineering for production LLMs — structured outputs, evals, RAG, tool workflows, multimodal prompting, and safety. Use when designing, debugging, or shipping prompts.
Quellsprache: Englisch
Diagnoses and tunes SQL for OLTP workloads on PostgreSQL, MySQL, and SQL Server. Use when tuning queries, reading plans, indexing, or fixing lock contention.
Quellsprache: Englisch
Measures AI coding impact and extension robustness. Use when tracking delivery, quality trajectories, cost, experience, pilots, scorecards, or leadership reporting.
Quellsprache: Englisch
Designs durable API contracts across REST, GraphQL, gRPC, tRPC, and AsyncAPI. Use when specifying interfaces, auth, versioning, errors, rate limits, or agent APIs.
Quellsprache: Englisch
Analyzes commit and PR history to score contribution quality objectively. Use when building engineering scorecards, calibrating promotions, or measuring AI-assist impact.
Quellsprache: Englisch
Designs team Git workflows for branching, PRs, and releases. Use when choosing branching models, stacked PRs, merge queues, worktree isolation for agents, or collaboration rules.
Quellsprache: Englisch
Writes PRDs and specs optimized for coding assistants. Use when authoring requirements or project context for Claude Code, Cursor, Copilot, or Codex.
Quellsprache: Englisch
Create/edit .docx files with styles, templates, comments, and extraction workflows. Use when asked to generate Word reports, contracts, proposals, or convert Word content.
Quellsprache: Englisch
Applies planning and search theory (A*, CSP, MCTS, STRIPS/PDDL, HTN) to agent design. Use when an LLM agent hallucinates action sequences or needs precondition/effect validity.
Quellsprache: Englisch
16 behavioral-economics primitives for ethical pricing, choice design, and retention. Use when framing, defaults, habits, dark patterns, AI-agent nudging, or nudge ethics apply.
Quellsprache: Englisch
Causal-inference primitives: DAGs, IV, RDD, DiD, synthetic control, propensity, CATE, interference. Use when attributing confounded impact or rollout and LLM-eval confounding.
Quellsprache: Englisch
Consumer-neuroscience primitives for attention, arousal, bonding, narrative, memory, and reward. Use when shaping ethical UX, neuro study design, or DMCC/AI Act gates.
Quellsprache: Englisch
Control-theory primitives for PID, MPC, Kalman, stability, anti-windup, dead-time, breakers, and limits. Use when tuning autoscaling, retries, or agent loops.
Quellsprache: Englisch
Applies Beer's VSM and Ashby's Law to diagnose org or agent-system viability. Use when a team or agent hierarchy has coordination, escalation, or requisite-variety problems.
Quellsprache: Englisch
Decision-theory primitives for uncertain choices, utility, Bayesian decisions, regret, value of information, MCDA, options, and bandits. Use when choosing under uncertainty.
Quellsprache: Englisch
Distributed-systems primitives for CAP/PACELC, FLP, Paxos, Raft, clocks, CRDTs, leases, quorums, and broadcast protocols. Use when designing coordination.
Quellsprache: Englisch
Game-theory primitives for strategic decision systems, auctions, mechanism design, incentives, attribution, negotiation, debate, and trust. Use when modeling strategic play.
Quellsprache: Englisch
Grounding-theory primitives for human-AI and agent handoffs, common ground, acceptance evidence, repair, and ambiguity. Use when coordinating meaning.
Quellsprache: Englisch
Information-theory primitives for AI systems, entropy, mutual information, KL, compression, channel limits, MDL, bottlenecks, and signal quality. Use when quantifying information.
Quellsprache: Englisch
Network-science primitives for graph systems, centrality, PageRank, communities, contagion, link prediction, and temporal networks. Use when analyzing graph structure.
Quellsprache: Englisch
Applies queueing theory (Little's Law, M/M/c, Erlang, Kingman, USL) to capacity and latency decisions. Use when load causes non-linear latency growth or queue overrun risk.
Quellsprache: Englisch
Reliability-theory primitives for MTBF/MTTR, availability, hazards, FMEA, redundancy, error budgets, Weibull analysis, and SLOs. Use when modeling failure.
Quellsprache: Englisch
Team-theory primitives for cooperative multi-agent decisions, subagent allocation, communication value, Dec-POMDPs, and decentralized control. Use when organizing agents.
Quellsprache: Englisch
Theory of Constraints primitives for focusing steps, drum-buffer-rope, throughput accounting, critical chain, and policy constraints. Use when sequencing by bottleneck.
Quellsprache: Englisch
Audits SaaS/PaaS, cloud commitment, and AI/LLM costs across Vercel, Supabase, AWS, and Cloudflare. Use when analyzing bills, right-sizing plans, or buying commitments.
Quellsprache: Englisch
Founder-PM toolkit for discovery, roadmaps, prioritization, and PMF measurement. Use when planning product strategy, metrics, or roadmaps.
Quellsprache: Englisch