@sickn33
chaos is order yet undeciphered zSUVXjYGMTwqSCgQ9GNiji2sBHFvYjB9U836chbpump
315 skills1 repository 48.3K
Create and edit Agent QA tests, test suites, and hooks, then validate their structure and tool-generated IDs before running them. Use MCP, an agent tool connection, or the CLI within a configured workspace.
Hand a scoped coding task to Aider while the coordinating agent reviews changes, runs project checks, and commits the result. Covers task briefs, execution tracking, and follow-up edits, but the executable helper is not bundled.
Generate, compose, and edit product images, posters, illustrations, and social graphics through the paid Beatra service. The workflow covers reviewing upload files and estimated costs before each paid call, then checking results and actual charges.
Find autonomous AI agents, frameworks, and tools through AgentFolio. Compare their capabilities, intended users, integrations, and deployment options to shortlist existing products or gather examples and ideas before designing an agent of your own.
Helps design focused AI products built on APIs such as OpenAI and Anthropic. Covers product strategy, prompts, model selection, user experience, usage tracking, and cost management for tools aimed at solving specific customer problems.
Create logo concepts from a brand name, industry, or reference image using Beatra’s paid service. The skill guides verified package installation, account authorization, cost approval, and review of the generated artwork.
Review GitHub Actions workflows that run AI agents, tracing how external input reaches prompts and tools. Produce findings with evidence, severity, impact, and remediation guidance through static analysis, which examines configuration without running attacks.
Create container-based hosted agents in Azure AI Foundry using Python and the Azure AI Projects SDK. Follow examples for resource settings, authentication, version management, and checks needed before treating a deployment as healthy.
Coordinate software development tasks across specialized agents for requirements, planning, architecture, implementation, review, testing, and deployment. Keep versioned reports, concise progress summaries, and open decisions organized, with user confirmation before moving between stages.
Coordinate multiple Claude Code workers through an existing Kanban board. This guide describes task dispatch, automated checks before AI review, per-task cost tracking, human intervention, and recovery after restarts; the runtime and integrations require separate installation.
Compare prompt revisions on a fixed set of test cases to identify regressions, meaning behavior that gets worse after a change. Record model settings, case-level evidence, missing results, costs, and evaluation limits for a reviewable decision.
Convert human-written CLAUDE.md instructions into a structured label format for AI agents. Use it to review lengthy rules, reduce instruction overhead, and prepare prompts for migration between AI tools while preserving the intended rules.
Generate realistic photo-style images with Google AI Studio for social posts and educational materials. Adjust aspect ratios, lighting, settings, and subtle imperfections to create a natural smartphone-photo look suited to each use.
Plan security controls for LLM applications and AI agents, covering malicious instructions, data leakage, model tampering, and API access. Includes guidance and code examples for filtering outputs, enforcing permissions, isolating networks, and recording audit events.
Plan AI application development by selecting relevant phases and companion skills. The workflow covers language model integration, retrieval from documents, agents, machine learning pipelines, monitoring, and security, with prompts and quality checklists.
Investigate failed Agent QA runs using recorded steps, logs, and saved evidence. Classify each failure, explain confidence and supporting findings, and identify the likely area to fix and the next action.
Plan reviews of AI-generated code before running or merging it. Define language-specific checks, tests in isolated environments, and evidence requirements, while recording coverage limits and gaps that prevent approval.
Set up recurring agent tasks using a supported scheduler, cron, or an authorized external timer. Choose a suitable cadence, preserve task state, prevent overlapping runs, define stop conditions, and verify that scheduled work runs as intended.
Inventory local skills within a requested scope, rank candidates against a task, and prepare a coordination plan showing their order and data flow. Project assignments help prioritize relevant skills without automatically launching agents or executing skills.
Design layered protections for AI agents against malicious instructions, tool misuse, and data leakage. Provides guidance and code examples for input checks, isolated tool execution, permission limits, and audit logging to help review and strengthen agent security.
Inspect local AI coding session logs with agenttrace to identify cost spikes, delays, failed tools, and retry loops. Produce readable reports, compare attempts, and configure automated checks for unusual or unhealthy runs.
Turn articles, notes, or scripts into solo podcast MP3s using the paid Beatra service. The referenced package supports a consistent host voice, natural pacing, and pronunciation control, with cost approval and audio review steps.
Build AI agents that make phone calls and send or receive SMS through the AgentPhone API. Manage phone numbers, configure voice agents and event notifications, and inspect call transcripts and account usage.
Guide a scoped coding task through specification, implementation, and review. Set acceptance criteria, verification checks, iteration limits, and approval gates, then correct identified gaps until the requirements pass or a stopping condition is reached.
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