opencode-power-pack

In the author's own words, from each skill's SKILL.md — showing the first 30 of 54 files.

• agentic-actions-auditor

  Audit GitHub Actions that run AI agents for prompt injection, unsafe interpolation, sandbox gaps, and permissive actor rules. Use for agentic CI workflows, not general application code review.

  skills/agentic-actions-auditor/SKILL.md on GitHub (opens in a new tab)

• agents-md-improver

  Audit and improve project-rules files (AGENTS.md, CLAUDE.md, .agents/instructions, local overrides) so the agent keeps accurate project context. Use when the user asks to check, audit, review, update, improve, or fix their AGENTS.md or CLAUDE.md, mentions "project rules maintenance" or "agent context optimization", or when the codebase has changed enough that the rules file may be stale. Scans th…

  skills/agents-md-improver/SKILL.md on GitHub (opens in a new tab)

• agents-md-revise

  Capture learnings from the current session into the project-rules file (AGENTS.md, CLAUDE.md, or local override) so future sessions benefit. Use when the user says "revise the rules", "update AGENTS.md / CLAUDE.md with what we just learned", "save this to project memory", "remember this for next time", or at the end of a productive session when valuable context has emerged that is not yet documen…

  skills/agents-md-revise/SKILL.md on GitHub (opens in a new tab)

• ai-slop

  Operational rubric that turns "don't make AI slop" into observable properties, severity levels, evidence requirements, and repair actions for interface design. Use as the reference rubric when building or reviewing marketing sites, product interfaces, dashboards, portfolios, or e-commerce pages, especially alongside frontend-design.

  skills/ai-slop/SKILL.md on GitHub (opens in a new tab)

• code-architect

  Design a feature architecture by analyzing existing codebase patterns and conventions, then provide a comprehensive implementation blueprint with specific files to create or modify, component designs, data flows, and a build sequence. Use this skill when the user asks for an architecture design, an implementation plan for a non-trivial feature, or when dispatched as a sub-task during feature-dev…

  skills/code-architect/SKILL.md on GitHub (opens in a new tab)

• code-explorer

  Deeply analyze an existing codebase feature by tracing execution paths, mapping architecture layers, understanding patterns and abstractions, and documenting dependencies. Use this skill when you need to understand how a feature works before modifying or extending it, when dispatched as a sub-task during feature-dev exploration, or when the user asks "how does X work in this codebase".

  skills/code-explorer/SKILL.md on GitHub (opens in a new tab)

• code-quality

  Agents should invoke this skill for code reviews, linting/formatting setup, maintainability checks, complexity concerns, warning cleanup, coding standards, or quality gates in Rust, TypeScript, Python, shell, and mixed repos.

  skills/code-quality/SKILL.md on GitHub (opens in a new tab)

• code-review

  Review a pull request or a set of code changes for bugs, logic errors, and project-convention violations using a confidence-filtered, multi-agent process. Use this skill when the user asks to review a PR, audit pending changes, or inspect a diff for problems before merging.

  skills/code-review/SKILL.md on GitHub (opens in a new tab)

• code-reviewer

  Review code for bugs, logic errors, security vulnerabilities, code quality issues, and adherence to project conventions, using confidence-based filtering to report only high-priority issues that truly matter. Use this skill when reviewing a small set of changes locally (such as unstaged diff), when dispatched as a sub-task during feature-dev quality review, or when the user wants a critique of a…

  skills/code-reviewer/SKILL.md on GitHub (opens in a new tab)

• codeql

  Run CodeQL database creation and security queries, add data-extension models, or process CodeQL SARIF. Use when CodeQL is explicitly requested; use security-review for a broader manual security review.

  skills/codeql/SKILL.md on GitHub (opens in a new tab)

• design-patterns

  Agents should invoke this skill when choosing patterns, designing traits/interfaces/components, deciding abstraction boundaries, evaluating dependency injection/callbacks, or comparing implementation approaches in Rust, TypeScript/React, or Django/Python.

  skills/design-patterns/SKILL.md on GitHub (opens in a new tab)

• differential-review

  Performs security-focused differential review of code changes (PRs, commits, diffs). Adapts analysis depth to codebase size, uses git history for context, calculates blast radius, checks test coverage, and generates comprehensive markdown reports. Automatically detects and prevents security regressions.

  skills/differential-review/SKILL.md on GitHub (opens in a new tab)

• feature-dev

  Guide a feature implementation through a structured seven-phase workflow with deep codebase understanding, clarifying questions, parallel architecture design, and quality review. Use this skill when the user asks to build a new feature, add functionality, or wants a methodical approach to implementation rather than diving straight to code.

  skills/feature-dev/SKILL.md on GitHub (opens in a new tab)

• fp-check

  Systematically verifies suspected security bugs to eliminate false positives. Produces TRUE POSITIVE or FALSE POSITIVE verdicts with documented evidence for each bug.

  skills/fp-check/SKILL.md on GitHub (opens in a new tab)

• frontend-design

  Create distinctive, production-grade frontend interfaces with high design quality and accessible markup. Use this skill when the user asks to build or beautify web components, pages, applications, landing pages, dashboards, artifacts, or React/HTML/CSS UI. Generates creative, polished code that avoids generic AI aesthetics, then self-checks it against an objective accessibility and quality rubric.

  skills/frontend-design/SKILL.md on GitHub (opens in a new tab)

• hf-cli

  Use the `hf` CLI for Hub authentication, downloads, uploads, repositories, cache, jobs, buckets, webhooks, and endpoint administration. Use for CLI operations, not model recommendations, paper analysis, training design, or building a Space.

  skills/hf-cli/SKILL.md on GitHub (opens in a new tab)

• hf-cloud-aws-context-discovery

  Discover the active AWS profile, region, account, and caller identity before SageMaker or AWS work. Use when local AWS context is needed or unspecified; do not use for cloud-agnostic model planning.

  skills/hf-cloud-aws-context-discovery/SKILL.md on GitHub (opens in a new tab)

• hf-cloud-python-env-setup

  Create an isolated Python environment with a compatible Python version and boto3 for SageMaker or AWS automation. Use before executing AWS Python code; do not use for general Python environment setup.

  skills/hf-cloud-python-env-setup/SKILL.md on GitHub (opens in a new tab)

• hf-cloud-sagemaker-deployment-planner

  Plan and coordinate a model deployment to Amazon SageMaker, including serving stack and real-time versus async inference. Use as the entry point for SageMaker hosting requests, before image, IAM, and endpoint implementation skills.

  skills/hf-cloud-sagemaker-deployment-planner/SKILL.md on GitHub (opens in a new tab)

• hf-cloud-sagemaker-iam-preflight

  Verify or select a SageMaker execution role before creating models, endpoints, or training jobs. Use when a role ARN is missing or IAM access fails; inspect existing roles before proposing role creation.

  skills/hf-cloud-sagemaker-iam-preflight/SKILL.md on GitHub (opens in a new tab)

• hf-cloud-sagemaker-production-defaults

  Implement a production SageMaker endpoint with autoscaling, CloudWatch alarms, and tags. Use after the serving image and IAM role are known; use the deployment planner first when architecture is undecided.

  skills/hf-cloud-sagemaker-production-defaults/SKILL.md on GitHub (opens in a new tab)

• hf-cloud-serving-image-selection

  Select and verify the current region-specific serving container URI for a SageMaker model deployment. Use after the deployment pathway is chosen and before endpoint code; never infer an image URI from memory.

  skills/hf-cloud-serving-image-selection/SKILL.md on GitHub (opens in a new tab)

• hf-mem

  Hugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face Hub.

  skills/hf-mem/SKILL.md on GitHub (opens in a new tab)

• huggingface-best

  Find and compare recommended Hugging Face models for a task using benchmarks, model size, and device constraints. Use for model selection questions; use huggingface-local-models for GGUF setup and hf-cli for Hub operations.

  skills/huggingface-best/SKILL.md on GitHub (opens in a new tab)

• huggingface-community-evals

  Run evaluations for Hugging Face Hub models using inspect-ai and lighteval on local hardware. Use for backend selection, local GPU evals, and choosing between vLLM / Transformers / accelerate. Not for HF Jobs orchestration, model-card PRs, .eval_results publication, or community-evals automation.

  skills/huggingface-community-evals/SKILL.md on GitHub (opens in a new tab)

• huggingface-datasets

  Use this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics.

  skills/huggingface-datasets/SKILL.md on GitHub (opens in a new tab)

• huggingface-gradio

  Build Gradio web UIs and demos in Python. Use when creating or editing Gradio apps, components, event listeners, layouts, or chatbots.

  skills/huggingface-gradio/SKILL.md on GitHub (opens in a new tab)

• huggingface-llm-trainer

  Train or fine-tune language models with TRL or Unsloth on Hugging Face Jobs, including SFT, DPO, GRPO, reward models, and GGUF conversion. Use for cloud LLM training; use huggingface-vision-trainer for vision tasks.

  skills/huggingface-llm-trainer/SKILL.md on GitHub (opens in a new tab)

• huggingface-local-models

  Use to select models to run locally with llama.cpp and GGUF on CPU, Mac Metal, CUDA, or ROCm. Covers finding GGUFs, quant selection, running servers, exact GGUF file lookup, conversion, and OpenAI-compatible local serving.

  skills/huggingface-local-models/SKILL.md on GitHub (opens in a new tab)

• huggingface-lora-space-builder

  Build and publish a Gradio Hugging Face Space for a user-provided image or video LoRA, including pipeline selection and model-card settings. Use for LoRA demos; use huggingface-spaces for general Space work.

  skills/huggingface-lora-space-builder/SKILL.md on GitHub (opens in a new tab)

No skill matches that filter.

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