2.1K skills · sorted by relevance
Turn a development goal into a focused ralph-loop command through conversation and codebase research. Define context, setup steps, ordered tasks, and testing criteria, then produce a complete command ready to copy.
Plan a Claude Managed Agent around one clear job, then route work through setup, launch preparation, evaluation, and scheduling. Produce execution plans and curl commands that users run with their own Anthropic API key.
Compare five growth loops, mechanisms where user activity brings in more users, to find a suitable approach for a product. Develop an implementation roadmap, measurement plan, and growth estimates based on sharing, collaboration, content, or referrals.
Run iterative development with repeated implementation and verification, using failure history to guide changes. When a verification command is configured, an independent hook checks completion after the agent's own tests, with pause and abort markers available.
Improve writing, prompts, or skills through repeated review cycles that carry forward lessons and rejected approaches. Human feedback guides each pass by default, while saved history supports resuming work and tracking progress.
Investigate recurring problems by mapping feedback loops, the cycles through which effects influence their causes. Identify underlying structures, match known patterns, and assess where changes could help and what unintended effects they might produce.
Set up recurring agent work for issues, tickets, or small fixes. The skill tests one real item first, then defines a repeatable procedure, tracks work to prevent duplicates, and holds outputs for human review.
Manage a project's stored materials through inventory, migration, archiving, and ranking based on verified source reads. Changes follow owner approval, preserve material references, and include validation records and rollback procedures.
Manage repeated work on a task in Codex with iteration limits, completion conditions, and saved progress. Advance iterations manually with the default engine, or use the optional open-ralph-wiggum command-line tool for automatic iteration.
Run, monitor, resume, merge, and debug Ralph loops. Use this skill whenever the user asks to operate `ralph run` or `ralph loops`, inspect loop state, recover suspended loops, analyze diagnostics, or unblock merge queue issues.
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Use when the user asks for Superloopy clone or asks to clone, rebuild, reverse-engineer, replicate, or copy a website or page into a Superloopy-governed implementation. Triggers on "loopy clone", target URLs plus requests such as "clone this site", "rebuild this page", "make a copy of this website", "pixel-perfect clone", or "AI website clone". Requires browser automation and records component specs, assets, implementation, build output, and visual QA as Superloopy evidence.
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Orchestrates end-to-end autonomous AI research projects using a two-loop architecture. The inner loop runs rapid experiment iterations with clear optimization targets. The outer loop synthesizes results, identifies patterns, and steers research direction. Routes to domain-specific skills for execution, supports continuous agent operation via Claude Code /loop and OpenClaw heartbeat, and produces research presentations and papers. Use when starting a research project, running autonomous experiments, or managing a multi-hypothesis research effort.
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Use when someone wants seamless looping motion graphics for video in their own brand colors: animated backgrounds behind titles, filler for the dead seconds between AI shots, bumpers, transitions or shape animations, built as code and rendered to MP4, optionally with their mascot, product or character from Scenario composited over the loop. Keywords: seamless loop, motion background, canvas animation, motion graphics, loop seam, motion blur, H.264 export, alpha composite.
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Autonomous multi-page site builder using a baton-passing loop. Each iteration reads a task from .design/next-prompt.md, generates a page in HTML/Tailwind, integrates it into the site, verifies visually, then writes the next task to keep the loop alive. Use whenever the user asks to build an entire site autonomously, build all pages of a site, generate multiple pages in sequence, or run a 'design loop' / 'baton loop' / 'autonomous site build' — even if they say 'just keep going' or 'build the next page' or 'next page' mid-flow.
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Design an adaptive assessment loop where each student response triggers the next instructional move. Use when building technology-enhanced formative assessment cycles.
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Universal discipline for any LM-driven loop — agent retries, plan-act-observe, multi-agent handoffs, optimiser passes, test-fix cycles. Encodes the one rule every framework documents quietly and every team relearns expensively: the LM in the loop is NEVER a reliable terminator. Termination must be provided by an explicit counter + exit predicate + stagnation signal + escalation path that live OUTSIDE the LM's control. This is a tool- level, framework-agnostic skill. It maps onto LangGraph (recursion_limit + state counter + interrupt), CrewAI (max_iter + max_rpm + human_input), Claude / OpenAI SDKs (max_iterations + tool_use_budget), DSPy (declared evaluation budget), Aider (REPL + explicit retry cap), and AutoGen (max_consecutive_auto_reply). Search keywords: infinite loop, recursion limit, recursion_limit, GraphRecursionError, max iterations, max_iter, agent stuck, agent won't stop, runaway agent, ReAct loop not terminating, agent repeating itself.
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Run a spec-driven agent loop where coding tasks live as markdown specs that move through inbox → active → archive, get implemented by Claude Code or Codex, and pass a review gate before they count as done. Use when the user mentions "loop factory", a "spec-driven loop", an "agent factory", wants repeatable/reviewable agent work, or when a repo has a factory/specs/inbox or factory/specs/active directory. Also covers installing and scaffolding the loop-factory CLI into a project.
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Interactive escalation-resolution workflow for the bmad-loop orchestrator. A bmad-loop run paused on a CRITICAL escalation (a contradiction or gap a dev/review session could not safely resolve alone); you and the human disambiguate the frozen spec so the story can be re-driven. Invoked as /bmad-loop-resolve <story-key>. Unlike the automated dev/review sessions this session is interactive — a human is present and you SHOULD ask.
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Use Superloopy's lightweight strict-evidence loop for Codex tasks that need durable progress, criteria, and artifact-backed completion.
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Use only after explicit Codex `$superloopy:i-have-adhd` or Claude Code `/superloopy:i-have-adhd` invocation, or when a qualifying leading `loopy`/`루피` task receives Superloopy's non-diagnostic ADHD-friendly output overlay. Do not activate from typos, fragmented writing, urgency, grammar, language proficiency, or ordinary discussion of ADHD, attention, focus, accessibility, or cognitive load.
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Design an adaptive assessment loop where each student response triggers the next instructional move. Use when building technology-enhanced formative assessment cycles.
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Orchestrate a named multi-skill loop such as /loop /review /fix until clean or blocked. Use when the user explicitly asks to loop skills, rerun a review/fix cycle, or says /loop with one or more skill names.
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Scaffold and run Karpathy-style autoresearch loops in any git repo. This skill should be used when setting up autonomous code improvement, generating adversarial eval harnesses, running hypothesis-implement-eval-keep/discard loops, or checking autoresearch progress. Triggers on "autoresearch", "autonomous improvement", "eval loop", "hypothesis loop", "self-improvement loop".
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Complete operational workflow for implementer agents (Codex, Gemini, etc.) making code changes and writing tests. Defines the Code Change Loop, Test Writing Loop, and Issue Filing process with circuit breakers, severity levels, and escalation rules. Includes bundled scripts for specialist-review (code review) and test-review-request (test audit) that delegate to Claude CLI. Use this skill when starting any implementation task.
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