Total 56,151 skills, AI & Machine Learning has 9353 skills
Showing 12 of 9353 skills
Use when creating a new skill, adding a skill to the user's setup, or the user says "make this a skill". All personal skills live in the arjit-skills monorepo and are symlinked into place.
MoltOffer candidate agent. Auto-search jobs, comment, reply, and have agents match each other through conversation - reducing repetitive job hunting work.
Convert PRDs to prd.json format for the Ralph autonomous agent system. Use when you have an existing PRD and need to convert it to Ralph's JSON format. Triggers on: convert this prd, turn this into ralph format, create prd.json from this, ralph json.
Build and deploy parallel execution via subagent waves, agent teams, and multi-wave pipelines. Use when the Decomposition Gate identifies 2+ independent actions or when spawning teams. NOT for single-action tasks or non-parallel work.
Enables continuous self-improvement through learning from failures, user corrections, and capability gaps. Integrates with QAVR for learned memory ranking.
Documentation-driven development specification that requires Agent to consult official documentation and examples before generating code or fixing bugs, including API verification processes, search strategies and MCP invocation rules. It is applicable to scenarios such as accessing third-party libraries, troubleshooting API errors, and version changes.
Engineering operating model for teams where AI agents generate a large share of implementation output.
Background context for the Housing Loan Tax Credit in the Japanese tax filing plugin. It includes eligibility requirements, credit limits, calculation rules, and interactions with furusato-nozei (hometown tax donation) for the current tax year. This skill is not user-invocable — Claude loads it automatically when responding to Housing Loan Tax Credit questions or calculations.
Orchestration workflow for orchestrator role ONLY. Use when: - Agent's role name (tmux pane title) is "orchestrator"
Integrate Azure AI Services, Azure OpenAI, and Cognitive Services.
Strategic planning with optional interview workflow
Capture user corrections and feedback after any skill runs, persist them as learned instructions, and silently apply them on future invocations. TRIGGER when: user gives feedback or corrections after a skill runs — e.g. "next time only show top 5", "always use bullet points", "don't include X", "from now on...", "remember to...". Also: "What have you learned about {skill}?", "Show skill tuning", "Clear skill tuning for {skill}"