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Found 2,126 Skills
interview the user to design an agentic control loop (sensor, controller, actuator under disturbances) tailored to their codebase, then build it as locally-runnable components plus a scheduled coding-agent workflow
Connect Claude Code to an existing Chrome browser via CDP (Chrome DevTools Protocol). Zero dependencies — uses Node 22 built-in WebSocket. Attach to any Chrome running with --remote-debugging-port, then navigate, click, type, screenshot, evaluate JS, read accessibility tree, and monitor console/network. Use when you need to interact with a browser the agent already started, control an existing Chrome instance, or drive browser automation without Playwright MCP. Triggers on: cdp connect, connect to browser, connect to chrome, attach to browser, interact with browser, drive browser, browser automation, control chrome, connect 9222.
Fundraising strategy for startups: fundability assessment against what VCs actually evaluate, the fundraising narrative and value proposition (positioning, why-now), round design (when to raise, how much, valuation, SAFE vs priced, dilution, milestones), term-sheet economics and negotiation, and devtools/AI-infra positioning (open source, platform risk, developer traction). Use when a founder asks whether or when to raise, how much and on what instrument, needs a value proposition or fundraising narrative, is weighing term-sheet terms, or must position a technical product for investors. Don't use for authoring deck slides (use vc-pitch-deck) or for running investor outreach, meetings, and pipeline (use vc-outreach).
Use when the user explicitly asks for Nerd Loop or wants a cost-proportional, behavior-aware task-completion controller that selects the cheapest adequate loop profile and iterates toward an explicit Definition of Done through focused work, automatic verification, and bounded stopping rules.
Execute tasks through competitive multi-agent generation, multi-judge evaluation, and evidence-based synthesis
Router over the workflow catalog. Ask which skill or flow fits your situation and get pointed at the right one. Use when unsure where to start.
Use when the user asks to "optimize entity presence", reconcile an entity identity, or update canonical Knowledge Graph facts; audits and maintains machine-facing identity, sameAs, schema, disambiguation, and AI-recognition evidence through the entities registry. Not for page-level AI-citation readiness - use geo-content-optimizer; not for human-facing brand canon - use narrative-registry. 实体注册/知识图谱
Test AI/LLM features that ship in your product. Covers prompt regression testing, response quality evaluation, tool-call validation, hallucination and RAG grounding checks, nondeterministic-output strategies, red-team/safety scans, eval frameworks, and agent-as-target injection (indirect injection via tool output / RAG / scan reports, self-propagating payloads, data exfiltration via an agent) plus a bundled detector for untrusted content. Use when: "test our LLM feature," "prompt regression test," "eval framework," "hallucination test," "RAG grounding," "nondeterministic output," "AI feature testing," "red-team our chatbot," "indirect prompt injection," "agent reading untrusted tool output," "production AI quality." Not for: using AI to generate your own test code — use ai-test-generation. Not for: classifying CI failures with AI — use ai-bug-triage. Not for: EU AI Act / GDPR conformity of an AI feature — use compliance-testing. Not for: canary/flag rollout of an AI feature — use testing-in-production. Related: ai-test-generation, ai-qa-review, api-testing, compliance-testing, security-testing, risk-based-testing, test-data-management.
Explore and optimize simulation parameters via design of experiments (DOE), sensitivity analysis, and optimizer selection — generate Latin Hypercube, quasi-random, or factorial sample plans, rank parameter influence with sensitivity scores, recommend Bayesian optimization, CMA-ES, or gradient- based methods based on dimension and budget, and fit surrogate models for expensive evaluations. Use when calibrating material properties against experimental data, planning a parameter sweep, performing uncertainty quantification, or choosing an optimization strategy for a simulation with a limited evaluation budget, even if the user only says "which parameters matter most" or "how do I calibrate my model."
Use when a developer asks their coding agent to initialize or work with moldea; plan an AI- or agent-enabled system and decide what should be agents versus deterministic software, services, tools, or human control; create or refine an AI agent or its behavioral system, including instructions, descriptions, handoff descriptions, tools, skills, schemas, variables and providers, routing or handoffs, bindings, or runtime integration; evaluate, reconcile, or validate an existing moldea system; or make ordinary behavior-affecting repository changes that may require maintaining an adopted moldea system. Loading the skill does not adopt moldea: initial adoption still requires explicit developer intent, while relevance-triggered maintenance applies once a repository uses or is adopting moldea.
Compare specs of 2–5 products side-by-side on Newegg. Use this skill whenever the user wants to compare products, see specs side by side, check differences between models, or evaluate options before buying — even if they don't say "compare" explicitly. Triggers: "compare these GPUs on newegg", "which is better RTX 4070 vs 4080", "比较这几个商品的规格", "side by side specs", "newegg compare", "help me pick between", "what are the differences between", "对比 Newegg 商品".
Analyze and improve content readability. Evaluate sentence complexity, word choice, and overall accessibility. Use when ensuring content is appropriate for target audience reading level.