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Found 6,591 Skills
Review AI-generated or human-written code changes with fallow's graph-grounded review brief. Subtracts deterministic concerns (unused code, complexity, duplication, styling) from the loop, ranks what to look at by blast radius and risk, and surfaces the few consequential structural decisions (new public-API contracts, coupling/boundary crossings, new dependencies) as framed judgment questions anchored to verifiable signals. Drives a closed agent-contract loop: fetch the walkthrough guide, return a judgment, and have fallow post-validate it against the live graph (hallucinated or stale judgments are rejected). Use when asked to review a PR, review a branch, review a diff, do a code review, or check changed code before merge.
Use for authorized security assessment of LLM applications and AI agents, including prompt injection, tool abuse, RAG exposure, memory poisoning, and model supply-chain risks.
Use for building, debugging, integrating, migrating, or documenting OpenUI, OpenUI Lang, Agent Interface, OpenUI Cloud, @openuidev packages, streaming generative UI rendering, component libraries, existing-project Cloud integration, Cloud BYOK, self-hosted-to-Cloud migration, migrations from JSON UI formats, Cloud tools (web/image search, artifacts), remote MCP servers, custom function tools and tool loops, and multi-user or multi-app identity (frontend tokens, app_id/user_id, conversation APIs, Responses metadata).
Interactive session to craft a system prompt for an AI agent powered by the Sanity Context MCP server. Use this skill when users want to define agent personality, set tone/voice, establish boundaries and guardrails, configure refusal behaviors, or control how their agent communicates. Trigger when users mention their agent sounds wrong, needs to refuse certain requests, has the wrong tone, or they want to set communication rules and policies.
Interactive session to create Instructions field content for the Sanity Context MCP server. Use this skill whenever users mention tuning agent context, improving agent responses to Sanity data, configuring MCP instructions, setting up content filters, or when their agent gives wrong results from Sanity queries. Also trigger when users say their agent is confused about schema relationships, needs data-specific guidance, or wants to optimize which content the agent can access.
(NS) Generate or refresh lean architecture-rules.md for AI agents — stack, layout, patterns, constraints. Use when the user asks for architecture rules, .nextstage-harness/rules/architecture-rules.md, agent conventions, or "document how this repo works for the AI". Do NOT use for business specs (ns-harness-codebase-reverse-spec), brownfield maps (ns-harness-bootstrap-brownfield), or one-off Cursor rules without a full architecture pass.
Work with the upstash-box Python SDK for sandboxed cloud containers with AI agents, shell, filesystem, git, cron schedules, and a headless browser. Use when building with Upstash Box in Python, creating sandboxed environments, running AI agents in containers, browser automation from a box, or orchestrating parallel boxes.
Use when deciding where knowledge goes or reading/writing durable docs: AGENTS.md, .context/, KB, docs/, and work directories.
Creative-writing domain knowledge for durable story state. Load when preserving or retrieving project memory — fact extraction, context scoping, reference writing, artifact layout, and issue tracking. If you are a knowledge agent such as kb-lead, load this for the fiction-specific categories and conventions your general methodology doesn't cover.
Active, Socratic teacher for the LangChain Academy Deep Agents course — drives the student through the curriculum with a calibrated interaction density, explain-then-check dialogue at load-bearing moments, and misconception-targeted questioning
Read Cursor / Claude Code / Codex agent logs and call write_knowledge for each durable learning found. Default auto-writes then reports what was cached and expected token savings (analytics-style: rediscovery/generation cost reused on each future read), and opens the HTML report. Dry-run lists the exact write_knowledge payloads (title, content, repo, branch) without writing. Use when the user says "Please bootstrap my knowledge with Dosu", "bootstrap agent knowledge", "/bootstrap-agent-knowledge", "log to dosu knowledge", "mine my sessions into Dosu", "backfill branch notes from my agent logs", "save my agent logs to Dosu", or wants a one-shot pass over local histories.
Use when long-running or parallel agent work must respect 5-hour and weekly usage limits by checking usage between waves, pausing near the cap, and resuming only when the window is clear.