Packs

8 packs

Loopyluci Skills

Loopyluci Skills from LoopyLuci/Skills.

100 skills · pack

@construct-ai-primary

Loopy AI from Construct-AI-primary/agent-companies-core.

3 skills · pack

Growth Loop Implementation

Identify the right growth loop mechanism, then build the acquisition and expansion motions to drive it.

3 skills · pack

Go-to-market skills for PMs: GTM strategy, growth loops, GTM motions, beachhead segments, and ideal customer profiles.

6 skills · pack

Build Agent with LangGraph

Build production-grade stateful AI agents using LangGraph, covering graph construction, state management, persistence, and human-in-the-loop patterns.

9 skills · pack

Build Agent UI in React/Next.js

Add a full agent interface to a React/Next.js app with streaming, human-in-the-loop approvals, and tool call UI.

3 skills · pack

Code-writing and execution skills for the Han suite. Home of the tdd skill, which drives a feature or behavior through a BDD-framed red-green-refactor loop with an enforced observed-failure gate. Depends on han-core and han-communication; bundled by the han meta-plugin.

11 skills · pack

@pwdev-solucoes

Framework de copy genérico e treinável v1.1 — um arquivo de contexto define marca, ICP e voz, e 20 skills cobrem o ciclo completo: pesquisa VOC, brand voice, criação (landing, social, ganchos, reaproveitamento), revisão em 7 sweeps com anti-slop, e camada de análise que fecha o loop; 5 subagentes reais

20 skills · pack

Results for “loop”

35 skills

Discover, find, compare, audit, repair, adapt, craft, run, debrief, and prepare repeatable AI-agent loops for publication. Use when a user asks to analyze code or coding threads for recurring work, find a published loop, interview them to turn a goal into a bounded loop, review a loop...

loop-design-check

Designs and reviews feedback loops for AI agents to ensure goals are machine-decidable, loops are damped, and human judgment is preserved.

Discovers, finds, audits, repairs, adapts, crafts, runs, debriefs, saves, and prepares repeatable AI-agent loops for publication, treating loops as bounded feedback systems.

Discover, compare, audit, repair, adapt, craft, run, debrief, and publish repeatable AI-agent loops for engineering workflows.

42.4k · bundle

Discover, audit, repair, adapt, and design bounded, verifiable AI-agent loops with explicit triggers, actions, stopping conditions, and guardrails.

20.4k · bundle

Discovers, audits, repairs, adapts, and designs bounded AI-agent loops with explicit triggers, actions, verification, stopping conditions, guardrails, and handoffs.

More results

loops-bounded-agent-loop-orchestration

Orchestrates bounded, governed iteration loops over existing agent commands and offices, with explicit stopping conditions, checkpoints, and honest terminal states.

Drafts structured goal-loop prompts for long-running agent work with verifiable stop conditions, validation commands, and documentation requirements.

sakamoto-family-smile

autonomous-loops

Patterns and architectures for running Claude Code autonomously in loops, from simple sequential pipelines to RFC-driven multi-agent DAG systems.

continuous-agent-loop

Provides patterns for continuous autonomous agent loops with quality gates, evals, and recovery controls.

Short alias that routes invocations to the vc-phase-loop skill for hands-off completion.

autonomous-loops

Run Claude Code autonomously in loops, from simple sequential pipelines to multi-agent DAG orchestration.

Runs a multi-agent adversarial verification loop where two independent reviewers must both pass before output ships, with a fix cycle for convergence.

Build production-grade stateful AI agents using LangGraph, covering graph construction, state management, persistence, and human-in-the-loop patterns.

securing-agentic-ai-tool-invocation

Apply least-privilege tool allowlisting, identity binding, and human-in-the-loop controls for agent tool calls.

24.6k · bundle

nimoqup046-collab

Build production-grade AI agents with LangGraph, covering graph construction, state management, reducers, conditional routing, checkpointers, and human-in-the-loop patterns.

orchestra-research

Orchestrates end-to-end autonomous AI research projects using a two-loop architecture for rapid experimentation and synthesis, producing papers and presentations.

10.4k · bundle

Add a batteries-included agent component to React/Next.js apps with runtime, streaming, human-in-the-loop approvals, and client-side tools.

gan-style-harness

Uses a multi-agent generator-evaluator feedback loop to build high-quality applications from a single prompt, inspired by GANs and Anthropic's harness design.

build-orchestration

Orchestrates a multi-agent build session, acting as manager to cut goals into units, spawn implementer and tester subagents, and run test-and-review loops with anti-thrash guardrails.

Defines an inter-agent communication protocol for C-suite agent teams, including invocation syntax, loop prevention, isolation rules, and response formats to coordinate cross-functional analysis and board meetings.

20.4k · bundle

self-improvement-loops

Designs and governs recursive self-improvement loops where an agent mines its own failures and proposes edits to its own harness, prompts, or workflow, covering acceptance gates, diversity preservation, and the optimization ladder.

16.9k · bundle

Spawns GLM-5 powered teammates with native thinking mode for coding, review, testing, planning, and research tasks.

Run autonomous optimization loops that iteratively improve artifacts against evaluators using hypothesis tree refinement, without overfitting.

30.2k · bundle

efficient-frontier

Orchestrate expensive frontier models as reviewers and cheaper subagents for bounded, token-heavy work to optimize cost and quality.

Implement iterative evaluation and refinement loops for AI agent outputs, using self-critique, evaluator-optimizer patterns, and rubric-based scoring to improve quality.

Runs an autonomous optimization loop that iteratively improves an artifact against an objective and evaluator using Hypothesis Tree Refinement, with subagent executors in isolated git worktrees.

continual-learning

Implements a continual learning loop for AI coding agents using hooks, two-tier memory (global and local), and automatic pattern detection to persist and apply learnings across sessions.

Implements AI safety guardrails including input validation, output filtering, robustness testing, human oversight, and monitoring to prevent harmful outputs and ensure system reliability.

Build multi-agent conversation systems with AutoGen, including two-agent chats, group chats, function calling, and nested conversations with code execution and human-in-the-loop options.

Access Google's most advanced AI models using the Gemini API in Agent Platform (formerly Vertex AI) with SDK installation, authentication, and code examples.

ai-automation-workflows

Build automated AI workflows combining multiple models and services for batch processing, scheduled tasks, event-driven pipelines, and agent loops using the inference.sh CLI.

orchestrating-llm-attacks-with-pyrit

Automate multi-turn adversarial conversations against LLM agents using Microsoft PyRIT, including Crescendo and Tree-of-Attacks-with-Pruning (TAP) attack chains with scorer feedback loops.

24.6k · bundle

tao-run-deft-aoi

Automates the full DEFT AOI improvement loop for NVIDIA TAO VisualChangeNet / ChangeNet PCB inspection models, including baseline evaluation, RCA, synthetic defect generation, data mining, retraining, and deployment gating until KPI targets are met.

Routes a research topic through a structured two-phase workflow: generate an extensible outline, then fan out parallel web-search agents to investigate each item into validated JSON, producing a complete markdown report with table of contents.