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Found 13,656 Skills
Commit the current agent's changes by default, or all working-tree changes when explicitly requested, with clean logical grouping and repository commit-message conventions. Use when the user asks to commit changes, commit this work, commit all changes, split changes into commits, propose commit messages, or wait for "go" before committing.
Bootstrap agents for iOS, iPadOS, macOS, Swift, SwiftUI, SwiftData/Core Data, Swift Testing, Xcode build/test/debug, Simulator, App Intents, or XcodeBuildMCP work. Use before building, fixing, refactoring, QAing, or setting up Apple-platform repos, and when asked to load/install Ray's iOS skills or bootstrap iOS.
Write, split, rename, or repair an agent skill so it activates when it should and can be proved rather than believed: a new skill, a description that never fires or fires on everything, a rule that has grown two decisions, an index that routes nothing an agent can see, a file too dense to read in one pass, or a check suite nobody has watched fail. Covers the activation surface, the routing gate, rule anatomy, page shape, naming, portability, and the invariant and mutation scripts. Use when the user says "write a skill", "this skill never triggers", "split this skill", "standardise these skills", or "how do I check this skill". Not for authoring product documentation, and not for deciding whether a task needs a skill at all.
Upgrade an installed Next Move Theory setup to the latest published canon + skills by re-running the official one-command installer, which clones the public GitHub repo (zamesin/Next-Move-Theory-Canon-and-Skills, branch main) and refreshes the canon, the nmt-* skills (both Claude and Codex), the injected rules block in CLAUDE.md / AGENTS.md, and the README — all in place. Idempotent and safe: it never touches your own files and never deletes unrelated skills. Use when the user says "update NMT", "upgrade the skills", "get the latest canon", runs /nmt-upgrade, or when another skill reports that a newer version is available. Defaults to English.
Run four parallel read-only subagents that each review the same diff from a different lens — security, performance, correctness, and readability — then merge findings into one report. Use before merging large or risky PRs.
Turns any goal into one short, paste-ready "gauntlet loop" prompt - a prompt that makes an agent set a concrete quality bar, split the work into small judgeable pieces, run a builder and a separate harsh critic on each, compare blind against the bar, and loop until it wins. Works for builds, writing, code, research, or design. Triggers on "/gauntlet-loop", "gauntlet loop", "gauntlet this", "make a gauntlet prompt", "loop until it beats X".
Set up state-of-the-art context engineering for any repository. Analyzes codebase, generates multi-level CLAUDE.md/AGENTS.md hierarchy, hooks, session management, and token budgets. Based on 200+ sources including ETH Zurich, Anthropic, Google DeepMind, and Manus production data. For engineers who ship with AI agents.
This skill is used when users want to review an existing code segment with an Agent — examining code rationality and identifying refactoring opportunities. It is language-neutral and focuses on design-level judgments (rather than correctness/mechanical checks). By default, it provides conversational conclusions and does not modify files proactively; hierarchical reports can be generated for archiving or large-scale code inspections, and findings can be reviewed item by item if there are multiple ones. Trigger: Users say "review / refactor / check if this code is reasonable / review with me / is there any problem with this design"; after writing a batch of code continuously, users or Agents can actively ask if inspection is needed. Not applicable: Executing single-point modifications with clear instructions from users (e.g., "change data1 to user_data"), adding new features, fixing bugs, performance tuning (profile/benchmark special projects), security audits, deterministic mechanical checks like lint, rewriting, or step-by-step inquiries (explaining code).
Use this skill when an agent needs to write reusable code, store it under the configured Hermes Code folder, run it directly through local code execution, or host it behind a Make-managed E2B Code Shell scenario. Use for tool-building, generated business automation scripts, and nested flows where hosted code calls Make API shell scenarios for SaaS access without receiving raw OAuth, Make, or E2B secrets.
Stand up (or extend) an operator-only in-app scratchpad / internal test-bed — a single gated internal page that reuses the project's real components and library functions so you can judge work-in-progress by eye: eyeball generated visuals (OG/social cards, emails, avatars, empty states), compare variants side by side or with live sliders, check config/env readiness, and exercise real side-effecting flows with fake data — without shipping any of it to users or clicking through the whole product. Boards and config panels get a "Copy as JSON" button so a tuned-by-eye result round-trips straight back into the code or to an agent to apply. Bootstraps into the user's existing stack: detects the framework, auth, and env conventions, writes a fail-closed access gate first, then a route with a section switcher seeded from their own code. Use when a user says "spin up a scratchpad", "internal test bed / dev playground / sandbox page", "an operator/admin preview page", "a page to eyeball my work", "preview my OG cards / emails / component variants", "add a test page for these components", or "an internal page to exercise a flow with fake data". NOT for public/user-facing features, NOT a replacement for tests (pass/fail machine-checkable → write a test), NOT Storybook (this lives inside the real app), and NOT a place to do load-bearing production operations.
Create, validate, and enrich Open Knowledge Format (OKF) bundles — the open spec for representing organizational knowledge as markdown files with YAML frontmatter. Use when the user mentions 'OKF', 'Open Knowledge Format', 'knowledge bundle', 'OKF bundle', 'create a knowledge base for agents', 'validate OKF', 'convert to OKF', 'enrich knowledge docs', 'agent-readable knowledge', 'LLM wiki', 'knowledge catalog', 'kcmd', or wants to structure knowledge as markdown files for AI agent consumption. Also use when the user has a directory of markdown files and wants to make them interoperable or conformant with the OKF standard. Even for simple requests like 'make this folder OKF conformant' — the skill has critical structural rules the agent needs.
When you want to create, adapt, or update a Claude Code skill in one of your sibling repos (list your own repos in ~/.config/makerskills/skillify/repos.yaml; defaults to makerskills). Routes to the right mode automatically. Modes — CREATE (from-chat / from-video / from-dump / from-scratch) turns a workflow, brief, recording, or fresh idea into a new skill. ADAPT ports an external skill (GitHub URL, agentskills.io, local disk) into your namespace with three-bucket classification (keep/adapt/add) + license check + attribution. UPDATE improves existing skills from learnings with cross-skill propagation, memory-vs-skill triage, and semver discipline. Defers to Anthropic's guidance (compound-engineering:create-agent-skill, compound-engineering:skill-creator, compound-engineering:heal-skill) for schema and best-practice depth. Triggers on "/skillify," "create a skill," "make this a skill," "skill from this chat," "extract a skill from what we've been doing," "adapt this skill," "port this skill," "fork this skill," "borrow this skill," "update X skill," "apply this to the relevant skills," "propagate this learning," "improve [skill]," "fix [skill]," "iterate on [skill]." Part of the -ify trifecta (skillify / toolify / loopify) for extending Claude Code.