Loading...
Loading...
Found 42 Skills
Configure and use the hosted YouTube Data MCP end-to-end with minimal user input. Use when users want the agent to verify Node.js and `npx`, configure MCP server config (Windows/macOS, Cursor/Codex/OpenClaw/OpenCode), request API key at setup time, run post-install capability discovery (`tools/list` and `get_patch_notes`), and then strongly recommend helper skill and Python setup for full local document and spreadsheet workflows.
Conduct a full-dimensional in-depth analysis of Amazon competitor Listings, including copywriting logic, review analysis, keyword analysis, market dynamics, etc. Automatically save the analysis as a Markdown report to the reports/ directory. Trigger this when the user uses the /amazon-analyse command with a product ASIN.
Use when starting infrastructure, testing, deployment, or framework-specific tasks - automatically searches PRPM registry for relevant expertise packages and suggests installation to enhance capabilities for the current task
Uncertainty-aware non-linear reasoning system with recursive subagent orchestration. Triggers for complex reasoning, research, multi-domain synthesis, or when explicit commands `/nlr`, `/reason`, `/think-deep` are used. Integrates think skill (reasoning), agent-core skill (acting), and MCP tools (infranodus, exa, scholar-gateway) in recursive think→act→observe loops. Uses coding sandbox for execution validation and maintains deliberate noisiness via NoisyGraph scaffold. Supports `/compact` mode for abbreviated outputs and `/semantic` mode for rich exploration.
Maximally Endowed Graph Architecture — λ-calculus over bounded n-SuperHyperGraphs with grounded uncertainty, conditional self-duality, and autopoietic refinement. Use when (1) simple graphs insufficient (η<2), (2) multi-scale reasoning required, (3) uncertainty is structured not stochastic, (4) knowledge must self-refactor. Pareto-governed: complexity added only when simpler structures fail validation.
Execute Google Gemini CLI for large-context code analysis, multimodal reasoning, and repository-scale reviews. Also use for delegating tasks requiring 1M token context windows or Gemini-specific capabilities.
Executable documentation governance with compound engineering and abductive learning. Enforces the Seven Laws through type compilation, schema validation, and hookify-based enforcement. Implements programmatic compound engineering where K' = K ∪ crystallize(assess(τ)) for monotonic knowledge growth. Integrates abstracted abductive learning (OHPT protocol) for systematic debugging and pattern extraction. Trigger when writing code, debugging, establishing governance, or when mentioned vibecode, compound, abductive, or executable documentation. Self-validating and homoiconic.
Routes analysis and debugging tasks. Triggers on analyze, debug, troubleshoot, review, audit, security, performance, optimize, investigate, trace.
Create distinctive, production-grade terminal user interfaces with high design quality. Use this skill when the user asks to build CLI tools, TUI applications, or terminal-based interfaces. Generates creative, polished code that avoids generic terminal aesthetics.
Compose intellectually sophisticated persuasive essays using tripartite dialectical structure (establish-critique-synthesize), paradox accumulation, conversational register calibration, and strategic humility. Supports three atomic writing primitives (AGONAL α, MAIEUTIC β, APOPHATIC γ) with hypersoft plithogenic composition, plus legacy style modes and hybrid combinations. Triggers on requests for persuasive writing to mixed/skeptical audiences, defending counterintuitive claims, Socratic pedagogical dialogue, editorial first-person essays, or writing that must balance accessibility with depth. Implements recursive thematic anchoring, forced dilemma construction, and transformed return closure. Use when linear argumentation is insufficient and accumulated tension resolves through synthesis.
Use when extracting entities and relationships, building ontologies, compressing large graphs, or analyzing knowledge structures - provides structural equivalence-based compression achieving 57-95% size reduction, k-bisimulation summarization, categorical quotient constructions, and metagraph hierarchical modeling with scale-invariant properties. Supports recursive refinement through graph topology metrics including |R|/|E| ratios and automorphism analysis.
The practice of restructuring and simplifying code continuously – reducing complexity, improving design, and keeping codebases clean.