Blank Agent Skill Template
A blank Markdown template for defining an Agent skill name, description, purpose, and instructions.
159 prompts
Tool choice, planning, state tracking, failure recovery, and task decomposition prompts.
A blank Markdown template for defining an Agent skill name, description, purpose, and instructions.
Use OpenCode CLI to scan, analyze, and integrate three GitHub repositories to enhance the local dev environment.
As a DevOps Engineer, set up Weights & Biases for experiment tracking and run a Kubernetes pod for model training, including secure SSH access and integration.
As a Vibe Coding Master, leverage AI tools to efficiently build commercial-grade applications, covering requirements analysis, framework configuration, coding, and testing.
Helps users identify automation opportunities, design efficient workflows, and integrate AI tools to optimize business processes.
Act as an interviewer for a software developer position in a one-on-one Q&A session.
Turn a coding task into the smallest, safest Claude Code loop primitive that runs until a verifiable stop condition is met.
Reconstruct prompt-heavy enterprise LLM prototypes into a traceable, auditable, code-owned agent architecture by moving behavior into manifests, schemas, validators, and runtime gates.
Design self-improving LLM agent context systems that treat context as an evolving playbook, using incremental deltas to defeat brevity bias and context collapse.
Evaluate AI agents by their control decisions and trajectory quality using a six-state taxonomy and failure taxonomy, not just final outcomes.
Designs safe maintenance routines for local AI coding agent state: inspect-before-mutate, archive-don't-delete, and continuity-preserving handoffs.
Optimize frozen-LLM skill documents with neural-network training discipline: rollout forward passes, reflection backprop, gradient clipping, and validation-gated acceptance producing deployable best_skill.md.
Assuming the null hypothesis, run a paired evidence-based audit to decide whether an agent skill actually improves a specific SWE task, weighing context interference and token cost.
Design the runtime, artifacts, constraints, and interfaces for metric-driven autonomous scientific discovery using off-the-shelf CLI agents.
Design memory subsystems for long-running agents as first-class data-management systems, covering representation, extraction, retrieval/routing, maintenance, and measurable evaluation.
Design an end-to-end cost-observability and budget-governance system for AI coding agents: cross-provider price normalization, real-time dashboards, budget gates, anomaly detection, and optimization loops.
Audit LLM agent trajectories using a six-state control-decision taxonomy, separating outcome success, control-decision quality, and trajectory quality.
A parallel divergent ideation skill for coding agents: spawns isolated branches under multiple cognitive frames, scores, clusters, prunes traps, and deepens top survivors.
Expand vague user requests across 5W3H intent dimensions into precise, cross-model-stable prompts.
Design production-grade event-driven frontend integrations with AI agents using the AG-UI protocol. Covers lifecycle events, streaming text, tool calls, state management, generative UI, human-in-the-loop patterns, and security.
Act as an A2UI architect who turns product requirements into secure, declarative, agent-generated UI designs using Google's A2UI open protocol, producing structured JSON contracts and component allowlists.
Design interoperable, asynchronous, and opaque agent-to-agent communication treating the A2A protocol as a binding contract, covering identity discovery, task lifecycle, protocol bindings, security boundaries, and versioning.
Distill a person's thinking style into a reusable agent skill: mental models, decision heuristics, expressive DNA, and honesty boundaries.
Designs cross-service automation workflows across Google Workspace (Drive, Gmail, Calendar, Docs, Sheets, etc.), emphasizing security, auditability, and reversibility.