Skills
15 skills publishedai-productivity
The AI Productivity skill acts as a high-performance intake layer for your agentic workflows. It identifies and resolves common execution bottlenecks before they waste tokens or time: vague prompts, overwhelming context "bloat," and high-risk ambiguous requests. Instead of diving blindly into a task, this skill triages the work, compresses relevant data, or rewrites instructions into actionable prompts.
truth-first-lite
The Truth-First Verification skill enforces a rigorous, evidence-based workflow for AI agents. It prevents "hallucinated certainty" by requiring real-time verification of system states, configurations, and file contents before the agent is allowed to provide an answer. Instead of assuming a service is running or a config is correct, the agent must prove it using available diagnostic tools.
pretext-layout
The Pretext Layout skill enables AI agents to integrate and debug high-performance multiline text measurement using the @chenglou/pretext library. It solves the common frontend performance bottleneck of "layout thrashing" by replacing slow DOM-based height probes with a fast, browser-native API approach.
prompt-engineer-lite
Building high-performance LLM applications requires more than just basic instructions. This skill equips your AI agent with a sophisticated framework for designing, debugging, and optimizing prompts across any major model provider. It solves the common problems of model drift, parsing failures, and hallucination by implementing industry-standard engineering patterns.
truth-first-enterprise
Enterprise-Grade Verification for Critical Decision Making In high-stakes environments like production operations, architecture reviews, and deployment gates, "hallucination" isn't just an inconvenience—it's a liability. This skill transforms your AI agent from a conversationalist into a disciplined technical auditor, ensuring every claim is backed by rigorous evidence before action is taken.
market-tech-analyst
The Market Tech Analyst is a specialized skill designed to bridge the gap between business strategy and technical execution. It provides a structured framework for evaluating new products, startup ideas, or feature initiatives by synthesizing market sizing with technical feasibility. Instead of providing generic advice, it delivers a rigorous breakdown of TAM/SAM/SOM estimates, technical dependencies, and competitive landscapes, all grounded in explicit assumptions and confidence ratings.
keyword-research
The Keyword Research skill transforms URLs, business descriptions, or product lists into professional-grade SEO strategy packs. It automates the heavy lifting of identifying seed topics, clustering keywords by intent, and prioritizing opportunities based on real Google signals. upported tools Google Ads API: Retrieves real-world search volume, CPC, and competition data. Python & PowerShell: Executes normalization and clustering scripts. Web Scraping: Extracts SEO signals from website headings
multi-agent-coordinator
Orchestrate Highly Complex AI Workflows Modern AI agents often struggle with "tunnel vision" when tackling large-scale engineering tasks. The Multi-Agent Coordinator skill solves this by transforming your agent into a project manager capable of breaking down complex, ambiguous, or high-risk tasks into specialized, narrow agent roles. Instead of one agent trying to do everything at once, this skill provides a framework for parallel processing and independent validation.
prompt-engineer-pro
Prompt Engineer Pro is a production-grade system for teams shipping AI workflows into business-critical environments. Unlike basic prompting assistants, this skill treats prompts as software assets that require governance, audit trails, and regression testing. It helps you build, audit, and harden prompt stacks for complex tasks involving multiple models, tool-use agents, and structured data extraction.
research-to-decision-pro-skill
The Research-to-Decision Pro skill transforms information overload into actionable clarity. It moves beyond standard "research dumps" by applying rigorous decision-making frameworks to compare options, evaluate tradeoffs, and provide a single, evidence-backed recommendation. Prompting an AI for a recommendation often results in vague summaries or "hallucinated" confidence. This skill enforces a structured logic chain that separates verified evidence from inferred assumptions.
business-planner
The Business Planner skill transforms vague commercial ideas into structured, data-driven execution plans. Most AI-generated business plans rely on generic strategy fluff; this skill forces a developer-like rigor onto business logic by treating assumptions as variables and outcomes as scenarios rather than certainties.
sun-tzu-business-strategy
This skill analyzes your business context through the lens of asymmetric competition, positioning, and timing. It maps your current situation to core principles—like resource concentration and the "path of least resistance"—to generate usable strategy memos. It doesn't just quote text; it bridges the gap between ancient theory and modern execution.
agent-permission-boundary-audit
This skill provides a comprehensive security and governance audit for AI agent systems. It analyzes tool inventories, authentication models, connector scopes, and execution logs to identify over-privileged tools and risky permission combinations.
harness-engineering
The Harness Engineering skill implements a structured methodology for agent orchestration. It allows you to build sophisticated control loops using a multi-role architecture: Planner: Defines contracts and stop rules. Executor: Performs bounded actions. Verifier: Validates results against evidence. Critic/Recovery: Identifies regressions and manages error state.
mesh flow
What it does Mesh Flow replaces fragile, implicit prompt-chaining with a robust, artifact-driven DAG (Directed Acyclic Graph) orchestration system. By defining your agent workflows in a structured project.yaml, you move logic out of the prompt and into a compile-time validated system. It enforces hard gates—such as human approval or dependency verification—that the AI cannot bypass or hallucinate past. Why use this skill Standard agentic workflows often fail because the LLM decides to skip steps or "forgets" requirements. Mesh Flow treats your agentic workflow like a CI/CD pipeline. It features a Compile-then-Run architecture that validates your topology for cycles and missing artifacts before single token is generated. This ensures 100% predictable execution paths, explicit failure states (failed, blocked, rejected), and absolute control over recovery paths. Supported tools YAML-based workflow configurations Standardized Adapter Interfaces for cross-skill communication Mermaid DAG visualization for debugging Zod-backed schema validation CLI tools for compilation and execution (mesh compile, mesh run) Output structure The skill produces a normalized execution plan and a detailed execution trace. Every node execution returns a standardized status, a list of produced artifacts, and comprehensive metadata including tool calls and verification reasoning. Use Cases Build multi-step agent pipelines with hard verification gates Enforce human-in-the-loop approval before sensitive code deployments Visualize complex agent task dependencies using Mermaid DAGs Standardize artifact sharing between disparate AI skills and agents