Packs

7 packs

PRD to Implementation Plan

Transform a raw product idea into a structured PRD and then into a technical implementation plan with issues.

11 skills · pack

Common base skills including documentation generators, implementation planning, and utility tools

7 skills · pack

Component Spec and Pattern Library

Document component anatomy, variants, and usage patterns for consistent implementation.

5 skills · pack

Growth Loop Implementation

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

3 skills · pack

Implement Plan with Git Workflow

Execute a predefined implementation plan step by step using isolated git worktrees and structured version control.

6 skills · pack

Planning skills for the Han suite: specifying, planning, sequencing, breaking down, and stress-testing work before implementation. Home of plan-a-feature, plan-implementation, plan-a-phased-build, plan-work-items, and iterative-plan-review, plus the discussion-facilitator agent. Depends on han-communication and han-core; bundled by the han meta-plugin.

5 skills · pack

Reporting and summary skills for the Han suite. Turns feature specifications into plain-language stakeholder summaries (also called executive or business summaries) with diagrams, for sharing with non-technical stakeholders before implementation kicks off.

2 skills · pack

Results for “implementation”

147 skills

Learn and apply CQL concepts, implementation strategies, best practices, and real-world applications in professional environments. Covers foundational concepts, Python implementation patterns, and production-grade system design.

breakdown-feature-implementation

Creates detailed technical implementation plans for features based on a Feature PRD, including system architecture, database schema, API design, and frontend component hierarchy.

create-github-issues-feature-from-implementation-plan

Create GitHub Issues from implementation plan phases using feature_request.yml or chore_request.yml templates.

structured-autonomy-implement

Executes a predefined implementation plan step by step, updating progress inline and running build or test commands.

nemo-automodel-model-onboarding

Guides implementation of new model architectures in NeMo AutoModel through five phases: discovery, implementation, registration, validation, and testing.

structured-autonomy-generate

Generates complete, copy-paste ready implementation documentation from a PR plan, including code blocks and verification checklists.

More results

Transforms a rough idea into a detailed design document with an implementation plan through iterative requirements clarification, research, design, and planning.

Use when tag expertise is needed to unblock implementation decisions.

Use when moc expertise is needed to unblock implementation decisions.

srednoff888-art

technical-writer-agent

Agent profile for write developer docs, user docs, API docs, tutorials, changelogs, and concise implementation notes. Use when Codex needs a specialist agent perspective for planning, implementation, review, debugging, validation, or handoff in this domain.

Audit specs against codebase — find unimplemented features, diverged implementations, and undocumented code

srednoff888-art

issue-to-pr-agent

Use this skill for turning issues into implementation plans, branches, code changes, tests, and PR descriptions. Trigger when the task involves programming work related to Issue To PR Agent, implementation, audits, debugging, strategy, or validation.

test-driven-development

Use when implementing any feature or bugfix, before writing implementation code

implementing-llms-litgpt

Implements and trains LLMs using Lightning AI's LitGPT with 20+ pretrained architectures (Llama, Gemma, Phi, Qwen, Mistral). Use when need clean model implementations, educational understanding of architectures, or production fine-tuning with LoRA/QLoRA. Single-file implementations, no abstraction layers.

implementing-llms-litgpt

Implements and trains LLMs using Lightning AI's LitGPT with 20+ pretrained architectures (Llama, Gemma, Phi, Qwen, Mistral). Use when need clean model implementations, educational understanding of architectures, or production fine-tuning with LoRA/QLoRA. Single-file implementations, no abstraction layers.

speckit-plan-agent

Execute the implementation planning workflow using the plan template to generate design artifacts.

[EXPLICIT INVOCATION ONLY] Creates dependency-aware implementation plans optimized for parallel multi-agent execution.

developer-development-rules

Design and implement clear, modular, resilient software and create executor-grade implementation plans with explicit scope, drift checks, verification gates, tests, STOP conditions, dependencies, and delegated-work review. Use for development, refactoring, architecture, implementation planning, safe migrations, handoffs to another engineer or agent, or verifying delegated code changes.

executing-plans

Executes a written implementation plan via per-batch sub-agent coordinators with verification and commits between batches.

executing-plans

Use when you have a written implementation plan to execute in a separate session with review checkpoints

Comprehensive guide to rag. Master the concepts, implementation, best practices, and real-world applications of rag in professional environments.

bmad-ml-hermione

Implementation specialist for LLM applications and AI systems. Use when the user asks to talk to Hermione, requests the AI engineer, or needs to build an LLM app or agent system.

Computes the LogAUC metric using the torchmetrics implementation for binary, multiclass, or multilabel classification tasks.

AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.

AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.

AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.

AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.

AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.

AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.

Use when you have a spec or requirements for a multi-step task, before touching code. Writes comprehensive implementation plans.

AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.

AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.

iamanacarolinarezende

AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.

AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.

AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.

AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.