Agent Workflow Claude Skills
4 122 agent workflow skills from 665 authors. They configure the agents themselves: memory, prompts, context and other skills. Half of them fit into 1 844 tokens or less — that is what one costs your context window when the agent loads it. 778 ship runnable scripts rather than instructions alone. 5 of them cannot work without an MCP server, most often task. We also found 589 copies of these same skills sitting in other people's repositories — counted once here, not 589 times.
4 122 unique 665 authors 4 updated this month 506 from vendors
When you want to set up an agent loop, cron-scheduled task, or recurring workflow that runs autonomously in Claude Code. Judgment layer on top of ScheduleWakeup, CronCreate, and the /loop skill — decides whether to use dynamic pacing (self-scheduling wake-ups), cron scheduling (fixed intervals), or a one-shot loop; tunes delay to avoid the 5-minute cache-miss cliff; designs idempotent loop bodies; sets bail-out conditions so loops don't run forever. Examples of loops to loopify — weekly review pulse, daily brief generation, hourly monitoring of a metric, periodic vault compilation, upstream-check for an adapted skill, sponsorship-pipeline refresh, YouTube-transcript-batch-download, morning startup routine. Triggers on "/loopify," "set up a loop," "schedule this task," "run this daily," "run this weekly," "cron this," "make this recurring," "automate this on a schedule," "keep this running until X." Part of the -ify trifecta (skillify / toolify / loopify) for extending Claude Code. NOT for authoring a new skill — that's skillify. NOT for adding a tool/integration — that's toolify.
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.
When a solution seems impossible and the path forward is blocked — the antidote to any roadblock or wall. Refuses to take no for an answer: classifies what kind of \"no\" you actually hit, then runs targeted lateral-thinking techniques (assumption autopsy, inversion, first principles, constraint toggling, analogical transfer, and more from a 10-technique inventory) until the wall cracks or is proven load-bearing. Generates a minimum of 10 angles before evaluating any. AGENTS: use this on yourself mid-task — when an API doesn't support what you need, an approach has failed twice, or a \"that's not possible\" / \"the only option is\" sentence is forming in your response, run the fast path BEFORE reporting a dead end; every dead-end report should arrive with tried-angles receipts. Archives every wall to ~/.config/makerskills/unstuck/archive/ so you learn which techniques crack YOUR walls. Sits upstream of decide: turns \"impossible\" into 2–3 viable angles, then decide picks one. Triggers on \"/unstuck,\" \"I'm stuck,\" \"this seems impossible,\" \"we hit a wall,\" \"there's no way to,\" \"they said no,\" \"dead end,\" \"out of options,\" \"I've tried everything,\" \"work around this,\" \"think outside the box.\
Core principle that the main agent is a coordinator, not an implementer. All work must be delegated to subagents.
Core Smart Ralph skill defining common arguments, execution modes, and shared behaviors across all Ralph plugins.
This skill should be used only when the user explicitly asks to use `$ralph-specum-design`, or explicitly asks Ralph Specum in Codex to run the design phase.
This skill should be used only when the user explicitly asks to use `$ralph-specum-index`, or explicitly asks Ralph Specum in Codex to generate or refresh index artifacts.
This skill should be used only when the user explicitly asks to use `$ralph-specum-requirements`, or explicitly asks Ralph Specum in Codex to run the requirements phase.
This skill should be used only when the user explicitly asks to use `$ralph-specum-tasks`, or explicitly asks Ralph Specum in Codex to run the tasks phase.
This skill should be used only when the user explicitly asks to use `$ralph-specum-triage`, or explicitly asks Ralph Specum in Codex to triage a large effort into multiple specs.
This skill should be used when running an interactive interview before a spec phase, gathering requirements through dialogue, asking the user clarifying questions before delegating to a subagent, or when any Ralph phase command (research, requirements, design, tasks) needs adaptive brainstorming dialogue. Covers the 3-phase algorithm (Understand, Propose Approaches, Confirm and Store).
This skill should be used when generating spec artifacts (research.md, requirements.md, design.md, tasks.md), formatting agent output, structuring phase results, or when any Ralph agent needs guidance on concise, scannable output formatting. Applies to all Ralph spec phase agents.
This skill should be used when the user asks about "ralph arguments", "quick mode", "commit spec", "max iterations", "ralph state file", "execution modes", "ralph loop", "coordinator behavior", "delegate to subagent", or needs guidance on Ralph plugin arguments, state management, delegation patterns, or execution loop behavior. Core behavioral skill for all Ralph Specum operations.
Use when you need to install the embedded robot agents into .github/agents, .claude/agents, .cursor/agents, or .codex/agents, selecting the destination interactively and copying the embedded agent definitions from project assets. This should trigger for requests such as Install embedded agents; Bootstrap .github/agents; Bootstrap .cursor/agents; Bootstrap .claude/agents; Bootstrap .codex/agents; Copy robot agents. Part of Plinth Toolkit
Use when you need to generate a checklist document with embedded agents inventory, following the embedded template exactly and producing INVENTORY-AGENTS-JAVA.md in the project root. This should trigger for requests such as Create embedded agents inventory checklist; Generate INVENTORY-AGENTS-JAVA.md; Use @002-agents-inventory; Inventory embedded Java agent definitions; List generated agent roles for Java development. Part of Plinth Toolkit
Use when you need to generate a checklist document with Java system prompts from skills.xml, following the embedded section template and producing INVENTORY-SKILLS-JAVA.md. This should trigger for requests such as Create Java system prompts checklist; Generate INVENTORY-SKILLS-JAVA.md; Use @003-skills-inventory; Inventory Java cursor rule skills; List available Java system prompt skills. Part of Plinth Toolkit
Use when you need to review a plan, OpenSpec change, specification, or implementation proposal for breaking-change risk across commands, skills, generated outputs, XML sources, README/docs, tests, CI, APIs, schemas, configuration, data, migration, and release guidance. This should trigger for requests such as Review breaking changes in this spec; Check compatibility risks; Avoid breaking changes in this OpenSpec change; Review migration impact before release; Assess command and skill compatibility. Part of Plinth Toolkit
Use when you need to generate an AGENTS.md file for a Java repository — covering project conventions, tech stack, file structure, commands, Git workflow, and contributor boundaries — through a modular, step-based interactive process that adapts to your specific project needs. This should trigger for requests such as Create AGENTS.md; Update AGENTS.md file; Add agent instructions; Generate contributor instructions for Java agents; Document repository conventions in AGENTS.md. Part of Plinth Toolkit
Use when you need framework-agnostic OpenAPI 3.x guidance — spec structure, metadata and versioning, paths and operations, reusable schemas, security schemes, examples, documentation quality, contract validation (e.g. Spectral), breaking-change awareness, and handoffs to codegen — without choosing Spring Boot, Quarkus, or Micronaut. This should trigger for requests such as Review an OpenAPI; Improve an OpenAPI; Improve API contract; Improve API schema design. Part of Plinth Toolkit
Use when reviewing, designing, or modifying Java enterprise systems that expose, exchange, store, process, export, or port data across users, businesses, connected products, cloud providers, APIs, event streams, AI data pipelines, data spaces, or SaaS platforms and need EU Data Act engineering controls. This should trigger for requests such as Review a Java platform for EU Data Act controls; Design data access and portability evidence; Add data-sharing request workflows, export formats, interoperability, metadata, audit logs, cloud-switching support, non-personal data safeguards, or trade-secret handoffs; Assess Data Act engineering readiness before production release. Part of Plinth Toolkit
Use when reviewing, designing, or modifying Java enterprise systems that use GenAI, LLMs, AI-assisted coding, RAG, AI agents, generated code, generated dependencies, prompt workflows, external model providers, or AI-enabled business logic and need ISO/IEC 42001 AI management system-aware engineering guidance. Part of Plinth Toolkit
Orchestrates a GitHub PR review loop by delegating triage and implementation to dedicated sub-agents, then repeating until actionable review items are cleared. Use when the user says “address PR review”, “triage review comments”, or “iterate until review is clean”.
> Multi-agent communication for AI coding tools. Agents message, watch, and spawn each other across terminals. Use when setting up hcom, troubleshooting delivery, or writing multi-agent scripts.
Switch a caller-selected coding-agent account and report the observed identity. Triggers: "switch account", "rotate coding-agent account".
Operate explicit orchestrator, implementer, validator, and scribe roles through a caller-selected agent runtime. Triggers: "agent-native factory", "role-shaped agent panes", "persistent workers".
Configure default Claude Code enforcement hooks and opt-in guard recipes. Triggers: "cc-hooks", "configure Claude Code hooks", "install hooks".
Front door for agent automation: choose inline, bounded fanout, reusable skill/workflow/gate, persistent agent-native workers, or explicit Gas City. Triggers: "build automation", "which orchestration shape", "should this use NTM".
Mine past agent sessions for working prompts, decisions, and patterns (session archaeology). Triggers: "cass", "mine past agent sessions for", "cass skill".
Use Agent Mail as an optional messaging and file-reservation adapter for explicitly coordinated writers. Triggers: "coordinate writers", "reserve files".
Convert AgentOps skill formats. Triggers: "converter", "convert agentops skill formats.", "converter skill".
Generate and validate repo docs, READMEs, and OSS doc packs. Triggers: "doc", "generate and validate repo docs", "doc skill".
Write compact caller-authored session evidence without choosing continuation. Triggers: "handoff", "write compact session handoff".
meta_skill (ms) — the skill-search/load engine over both corpora (agentops + jsm). Find a skill for a task, search skills, or load runnable skill guidance. Triggers: "ms", "meta_skill", "skill search", "find a skill for", "load skill guidance".
Distill repeated, evidence-backed expertise into a proposed skill, check, reference, or workflow artifact. Triggers: "operationalize this", "turn this expertise into a reusable capability".
Create a metadata-complete AgentOps skill source package, regenerate its derived projections, and check or repair structural hygiene in skill packages. Triggers: "create a skill", "scaffold skill", "absorb external skill", "new skill", "heal skill", "repair skill hygiene", "audit skill structure", "check skill package".
Operate the Agentic Coding Flywheel as a caller-selected software factory; keep its runtime state out of AgentOps verdicts. Triggers: "using flywheel", "agent flywheel".
Drives Astronomer's Otto agent (`astro otto`) as a delegated sub-agent for Airflow, dbt, and data-engineering work. Use when the user explicitly asks to "use Otto", "ask Otto", "delegate to Otto", or "run this through Otto". Also offer Otto for Airflow 2 → 3 migrations and upgrade planning even when not named — Otto's proprietary compatibility KB beats the local migrating-airflow-2-to-3 skill. Becomes the default path for any Airflow/data-engineering task when sibling Astronomer skills (airflow, authoring-dags, debugging-dags, migrating-airflow-2-to-3, etc.) are NOT loaded in the current session. Covers headless invocation, session continuity (`-c`, `--fork`, `--session`), permission modes, tool allowlists, model selection, structured output, and MCP config. **Do not load this skill if you are Otto** — Otto must not delegate to itself.
Guide for migrating Apache Airflow 2.x projects to Airflow 3.x. Use when the user mentions Airflow 3 migration, upgrade, compatibility issues, breaking changes, or wants to modernize their Airflow codebase. If you detect Airflow 2.x code that needs migration, prompt the user and ask if they want you to help upgrade. Always load this skill as the first step for any migration-related request.
Generate headless Claude Code cron jobs with safety.
Evaluate agents and skills for quality and standards compliance.
A/B test agent variants for quality and token cost.
Scaffold vexjoy-agent operator .md files: frontmatter, routing block, operator context, reference loading table, phase/gate workflow.
Classify user requests and route to the correct agent + skill. Primary entry point for all delegated work.
Analyze agent/skill reference depth and generate missing domain-specific reference files.
Maintain /do routing tables when skills or agents change.
Query and display structured decision traces from routing, agent selection, and skill execution.
DAG-based multi-skill orchestration with dependency resolution.
Create and iteratively improve skills through eval-driven validation.