codex-claude-code-config

In the author's own words, from each skill's SKILL.md — showing the first 30 of 60 files.

• agent-harness-design

  Designing agent harnesses and tool systems — risk taxonomy for tools, permission decisions, draft/commit pattern, structured tool results, agent budgets (10 types), context trust labels against prompt injection, plan-artifact, approval records, observability and traces, evals (13 categories), event model, streaming buffering, 3rd-party skill install checklist, agentic RAG, self-improving SOP loop…

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

• agents-best-practices

  Use when designing, auditing, refactoring, or explaining an agentic harness for any domain, especially when work must continue from a measured gap to verified completion. Covers provider-neutral loops, tools, permissions, environment adaptation, planning, durable workflow state, context, skills, observability, evals, and safety for OpenAI, Anthropic, and compatible APIs. Not for implementing an o…

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

• lean-code

  On-demand minimalism intensifier — find the smallest sufficient, verified implementation for the requested outcome. Use when the user says "be lazy / yagni / simplest / minimal / shortest / don't over-engineer", complains about bloat / boilerplate / unnecessary dependencies / abstraction, or before writing a substantial chunk of new code. Supports intensity: lite / full / ultra. Pairs with the al…

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

• plan-to-tickets

  Use when a large plan, PRD, feature, refactor, research plan, or multi-step coding task must be split into small ready-for-agent tickets with acceptance criteria, verification commands, blockers, and vertical tracer-bullet slices. Do not use for small tasks that should be implemented directly, single-bug fixes, or chat-only summaries.

  skills/plan-to-tickets/SKILL.md on GitHub (opens in a new tab)

• diffusion-engineering

  Практическая инженерия диффузионных моделей: архитектуры, обучение, инференс, оптимизация памяти. Использовать при любых задачах с диффузионными моделями: проектирование или модификация архитектуры (UNet/DiT/Flow/Flux), выбор и настройка schedulers/samplers, дообучение (LoRA/DreamBooth/full fine-tune), оптимизация памяти (AMP/checkpointing/ZeRO/FSDP/quantization), замена или fusion текст-энкодеро…

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

• flux2-klein-prompting

  Expert prompt engineering for FLUX.2 [klein] image generation and editing model. Use this skill whenever the user wants to create prompts for FLUX.2 [klein], generate images, edit photos with the klein model, work with multi-reference image editing, or needs templates for T2I/I2I tasks. Trigger for any mention of: FLUX.2, flux klein, BFL API, image editing prompts, text-to-image prompts for FLUX,…

  skills/ai-ml/flux2-klein-prompting/SKILL.md on GitHub (opens in a new tab)

• flux2-lora-training

  Plan or review LoRA and edit-training work specifically for FLUX.2 Klein or Qwen-Image-Edit, including paired datasets, trainer-version contracts, and held-out fidelity checks. Do not use for generic Stable Diffusion/DiT training, prompt authoring, or model serving; route those tasks to their specialized skill.

  skills/ai-ml/flux2-lora-training/SKILL.md on GitHub (opens in a new tab)

• forensic-prompt-compiler

  Forensic image-to-prompt compiler for image generation models. Use this skill whenever the user wants to: convert/describe an existing image into a generation prompt, reconstruct a scene as a prompt, generate prompts from reference images for AI image tools (Midjourney, FLUX, Stable Diffusion, DALL-E, or any diffusion model), write prompts that preserve exact visual properties of a source image,…

  skills/ai-ml/forensic-prompt-compiler/SKILL.md on GitHub (opens in a new tab)

• ml-research-lab

  Machine-learning research loop for dataset curation, fine-tuning, evaluation, inference deployment, experiment tracking, and model explainability. Use when working on ML experiments, training data, model benchmarks, RunPod/GPU runs, classifier quality, vLLM/GGUF serving, SHAP-style model explanations, or research-to-code iterations. Do not use for a simple code edit that has no ML dataset, metric…

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

• notebooklm-grounded-research

  Use when: NotebookLM, notebooklm MCP, large documentation sets, courses, books, papers, or citation-backed research are mentioned. Retrieves a small grounded answer from a stable corpus, preserves citations, and verifies claims against primary documentation, repository code, and tests. Do not use when: the answer is already in a small local file, the source is rapidly changing, or a live runtime/…

  skills/ai-ml/notebooklm-grounded-research/SKILL.md on GitHub (opens in a new tab)

• vlm-segmentation

  Choose and evaluate VLM or segmentation pipelines, including text-conditioned detection, masks, part labels, model-license constraints, and measured GPU deployment choices. Use when a task has a VLM or segmentation component; route pure diffusion prompting, training, or serving to its specialized skill.

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

• feature-new

  Scaffold a feature narrative in an existing project layer with Design, Plan, Verify, and Conclusion sections. Use when: "create a new feature", "start work on feature", "scaffold feature doc", "/feature-new", or "begin feature narrative". Inspects and preserves the target project's feature ID, registry, filename, and coordination conventions; does not create a missing layer (use /layer-new).

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

• harness-design

  Design a scoped multi-agent harness for a requested long-running AI workflow. Preserve the user-approved product boundary while using Generator-Evaluator separation, testable sprint contracts, context management, and task-appropriate validation. Based on Anthropic Engineering patterns. Use when: "build a harness", "multi-agent architecture", "agent orchestration", "generator-evaluator", "long-run…

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

• layer-new

  Scaffold a new layer in a project's docs/layers/ tree following the feature-layer architecture (principle 28). A layer is a bounded concern (security, data, ui, infrastructure, domain) with its own invariants, decisions, gotchas, patterns, and feature narratives. Use when: "create a new layer", "add security layer", "scaffold layer", "start tracking <concern> separately", "/layer-new", "add bound…

  skills/architecture/layer-new/SKILL.md on GitHub (opens in a new tab)

• plan-swarm-review

  Iterative plan review using multisampling + focused decomposition. Launches parallel independent agents to find issues that single-pass review misses. Up to four bounded rounds: broad, multisample, focused, focused-plus-multisample. Use when: "swarm review", "review plan thoroughly", "multisample review", "deep plan review", "plan swarming", "stress test the plan", or when evidenced cross-compone…

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

• pixel-art-storyboard

  Convert short scene descriptions, book/album cover briefs, or 2-paragraph synopses into seamless-loop animated pixel-art covers rendered as self-contained HTML+canvas. Companion skill to pixel-art-studio. Use when the user asks to "make a cover for", "animated book cover", "looped pixel scene", "convert this story description to pixel art", "create ambient pixel animation", "обложка для книги в п…

  skills/creative/pixel-art-storyboard/SKILL.md on GitHub (opens in a new tab)

• pixel-art-studio

  Create production-quality pixel art and animations programmatically. Use when the user asks to "create pixel art", "draw a sprite", "make pixel animation", "generate sprite sheet", "convert image to pixel art", "pixelate this image", "make a pixel character", "пиксель арт", "пиксельная графика", "спрайт", "像素画", "像素艺术", "도트 그래픽", "픽셀 아트", "8-bit/16-bit/hi-bit style", "retro game art", "Aseprite-l…

  skills/creative/pixel-art-studio/SKILL.md on GitHub (opens in a new tab)

• architecture-first

  Decide module boundaries before the first file: what modules exist, which way dependencies point, who owns state, and what each module may know. Use when starting a project, service, site, API, or subsystem; adding a feature with no obvious home; resolving a circular import or inverted framework dependency; or writing an ARCHITECTURE.md or ADR. Do not use for a one-file script, throwaway experime…

  skills/development/architecture-first/SKILL.md on GitHub (opens in a new tab)

• architecture-quality

  Keep web applications, APIs and services readable as they grow: choose feature or domain seams, assign state ownership, enforce dependency direction, keep adapters thin, and verify file shape. Use when starting or extending a web app, backend, frontend, API or multi-page product; when a change makes a module hard to read; when architecture review finds a god file, cross-feature imports, a circula…

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

• bug-reproducer

  Find likely software bugs in a codebase, rank concrete bug candidates, and prove or reject them with focused regression tests before proposing a fix. Also turn bug reports, stack traces, screenshots, failing behavior, support tickets, and regressions into minimal reproducible cases with red-to-green evidence. Use when Codex needs to hunt for unknown bugs, audit code for correctness defects, test…

  skills/development/bug-reproducer/SKILL.md on GitHub (opens in a new tab)

• code-complexity

  Keep each unit comprehensible while the code grows: deep modules over shallow ones, information hiding, honest names, small functions with one job, error handling that does not lose the error, DRY and orthogonality, design by contract, and not leaving broken windows. Merges module-complexity management with naming/function/error-handling discipline and the pragmatic meta-rules. Use when writing o…

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

• control-cli

  Drive and inspect an interactive CLI or TUI with a repeatable local harness, deterministic input, transcripts, and optional profiling. Use for CLI UX checks, prompt flows, startup regressions, hangs, interrupts, resize behavior, or memory growth. Do not use for a non-interactive command that a normal test can cover.

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

• control-ui

  Drive and inspect a local web, IDE, or Electron UI with browser or CDP automation and evidence. Use for UI regressions, screenshots, accessibility snapshots, visual diffs, focus, keyboard, scrolling, resize, console, network, performance, or heap checks. Do not use for backend-only changes or for a screenshot without a behavior claim.

  skills/development/control-ui/SKILL.md on GitHub (opens in a new tab)

• deep-review

  Parallel competency-based code review. Launches independent Agent reviewers per competency (security, performance, architecture, database, concurrency, error-handling, frontend, testing), each with a focused checklist and isolated context. Synthesizes findings into unified report with FIX/DEFER/ACCEPT triage. Use when: "deep review", "thorough review", "parallel review", "review by competency", "…

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

• deslop

  Remove AI-generated code noise from the current diff while preserving behavior. Use for deslop, AI slop cleanup, unnecessary comments, defensive checks, any casts, or needless nesting after an agent-generated change. Do not use as permission for a broad rewrite or when a real bug has not been isolated.

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

• distill-feedback

  Turn captured user-correction signals into durable rules (learn-from-corrections loop). Use when - /distill-feedback, "process feedback queue", "what corrections did I give you", "encode lessons from my corrections", session-feedback-capture queued sessions, "обнови правила по моим поправкам", "разбери очередь обратной связи". Reads ~/.claude/feedback/queue.jsonl, LLM-semantically detects durable…

  skills/development/distill-feedback/SKILL.md on GitHub (opens in a new tab)

• harness-feedback

  Use when an agent says a test, VM, proof, evaluator, or release gate is overloaded, too strict, blocking staging, or causing false positives; split checks by profile, measure the burden, preserve high-risk evidence, and verify the smallest corrected workflow. Do not use for ordinary test selection, a single test failure, or a full security audit without a harness-scope question.

  skills/development/harness-feedback/SKILL.md on GitHub (opens in a new tab)

• proof-verify

  Plan-based verification - freeze acceptance criteria before building, then verify after with an independent fresh-context agent (the builder must not verify their own work). For multi-stage work, seal accepted inputs with commit/tree, contract, input/output digests, and a fresh verdict so downstream stages do not reopen them. Use when - "verify against plan", "proof check", "independent review",…

  skills/development/proof-verify/SKILL.md on GitHub (opens in a new tab)

• refactoring-safely

  Change the structure of code that already exists without changing what it does: smells as triggers, the named transformations (extract/inline, move feature, organise data, simplify conditionals), and above all the workflow that makes it safe — characterization tests first, one transformation at a time, green between every step. Use when a file or function is already too large; when asked to "spli…

  skills/development/refactoring-safely/SKILL.md on GitHub (opens in a new tab)

• repo-map

  Ranked symbol map of a codebase within a token budget — a compact "what matters in this repo" before reading files. Use when starting work in an unfamiliar/large codebase, before a refactor or deep-review fan-out, when you need JIT context instead of dumping whole files, or asked "give me a map of this repo / where are the important functions / what's the structure". Zero-dependency (stdlib only)…

  skills/development/repo-map/SKILL.md on GitHub (opens in a new tab)

No skill matches that filter.

Similar skills

• ECCby affaan-m The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Cod… 280k stars · 30 skills
• unlazyby Leonxlnx Anti-laziness skill for AI agents. Core: the Depth Tree method, which splits a task N layers deep and gives every leaf the full time budget… 3.9k stars · 1 skill
• ponytailby DietrichGebert Makes your AI agent think like the laziest senior dev in the room. The best code is the code you never wrote. 164k stars · 6 skills
• cavemanby JuliusBrussee 🪨 why use many token when few token do trick. Viral skill + proxy for coding agents that cuts 65% of tokens by talking like a caveman. 113k stars · 20 skills
• awesome-claude-skillsby ComposioHQ A curated list of awesome Claude Skills, resources, and tools for customizing Claude AI workflows 77.2k stars
• marketingskillsby coreyhaines31 Marketing skills for Claude Code and AI agents. CRO, copywriting, SEO, analytics, and growth engineering. 54.9k stars · 30 skills