Results for “e-e-a-t”

Write a PRD or feature spec that aligns design and engineering — problem with evidence, explicit non-goals, measurable success metrics, and testable acceptance criteria.

Requires python3, and AISA_API_KEY. Uses the supplied AISA_API_KEY to send requests to https://api.aisa.one. Native-first ClawHub plugin for `tavily-extract`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. Extract clean, readable content from one or more URLs using Tavily Extract via AIsa API. Useful for reading full articles without visiting the page. Use when: the user needs web search, research, source discovery, or content extraction.

You are an expert in Clay, the data enrichment and outbound sales platform that pulls from 75+ data providers to build rich prospect profiles. You help teams automate lead discovery, enrich contacts with firmographic and technographic data, score leads against ICP criteria, and trigger personalized outreach sequences — replacing manual research with automated, data-driven prospecting.

Audits and rewrites user-facing copy across web and mobile codebases, improving clarity, tone, and actionability of labels, errors, CTAs, and empty states.

Reads a plan document, decomposes it into steps, designs a per-step agent chain from the ECC catalogue, and emits ready-to-paste /orchestrate custom prompts without executing them.

Extract clean, readable content from one or more URLs using Tavily Extract via AIsa API. Useful for reading full articles without visiting the page. Use when: the user needs web search, research, source discovery, or content extraction.

Decode an incoming message into a structured breakdown that separates the literal ask from the job-to-be-done, before replying to a loaded Slack ping, email, mandate, or escalation.

Craft clear, empathetic end-of-life announcements for products, features, or plans, including rationale, customer impact, and transition support.

Synthesize user research into a 4-quadrant empathy map (Says, Thinks, Does, Feels) to capture and share user understanding across a team.

Guides the end-to-end cyber threat intelligence lifecycle from planning and direction through collection, processing, analysis, dissemination, and feedback to establish or mature a CTI program.

Defines when to create Epic, Feature, UserStory, or Task tickets and adds concise guidance to SKILL.md.

Builds, edits or analyzes Agent Skills through conversational discovery. Use when the user requests to "Create an Agent", "Analyze an Agent" or "Edit an Agent".

Builds, edits or analyzes Agent Skills through conversational discovery. Use when the user requests to "Create an Agent", "Analyze an Agent" or "Edit an Agent".

Builds, edits or analyzes Agent Skills through conversational discovery. Use when the user requests to "Create an Agent", "Analyze an Agent" or "Edit an Agent".

Analyzes development requirements and generates structured acceptance criteria for AEM Edge Delivery Services tasks, including task breakdowns and edge case identification.

Optimize post-signup onboarding, user activation, first-run experience, and time-to-value with actionable audits and flow designs.

Frame an epic as a testable hypothesis with target user, expected outcome, and validation method. Use when defining a major initiative before roadmap, discovery, or delivery planning.

Install and route through OpenSpace, the skill management layer for AI agents, so a host agent can retrieve/rank/load the right SKILL.md out of this jeo-skills catalog (~150 installed skills), then evaluate skill quality from real execution evidence and evolve skills via FIX/DERIVED/CAPTURED updates. Covers install-as-skill-finder, retrieve-a-skill, evaluate-quality, evolve-skills, and local-first hub share/import. Triggers on: openspace, skill finder, skill retrieval, find the right skill, rank skills, skill discovery, skill quality, evolve skill, FIX DERIVED CAPTURED, skill hub, openspace-mcp, DiscoverSkills, skill-discovery, delegate-task.

Provides frameworks for international market expansion, including market selection, entry modes, localization, and go-to-market strategy.

Workflow 1.5: Bridge between idea discovery and auto review. Reads EXPERIMENT_PLAN.md, implements experiment code, deploys to GPU, collects initial results. Use when user says "实现实验", "implement experiments", "bridge", "从计划到跑实验", "deploy the plan", or has an experiment plan ready to execute.

Adopt the voice and methodology of Spotify's Daniel Ek to guide product strategy, marketplace design, and iterative growth decisions.

Helps identify and evaluate communities to build a minimalist business around, based on the philosophy of The Minimalist Entrepreneur.

Optimize electricity and gas procurement, tariffs, demand charges, renewable PPAs, and multi-facility energy costs using market analysis, hedging strategies, and load profiling.

Applies the BIZBOK enterprise architecture framework to structure analysis, problem solving, and decision documentation.

Conducts comprehensive network penetration tests against authorized target environments using host discovery, port scanning, service enumeration, vulnerability identification, and controlled exploitation following PTES methodology.

Generates a structured 6-minute two-person English product presentation script, split into unique features/target customers and market comparison/competitive advantages, with time allocations and full dialogue.

Turn assumptions, funnel opportunities, and product questions into a prioritised, feasibility-checked experiment backlog. Filters by traffic reality, metric latency, and method feasibility — not just ICE/RICE scoring. Maintains a living portfolio with status (idea → designed → running → readout → archived). Load when the user says "what should we test next", "build an experiment backlog", "prioritise our tests", "where should we experiment", "what's worth testing", or when the experimentation orchestrator routes here.

Operate execution flow across GitHub and Linear by triaging issues and pull requests, linking active work, and keeping GitHub public-facing while Linear remains the internal execution layer.

Estimate market size using TAM, SAM, and SOM with top-down and bottom-up approaches for market opportunity assessment, investor pitches, or market entry evaluation.

Perform semantic search, find similar content, and conduct structured research using the Exa API.

Turn a refined research proposal or method idea into a detailed, claim-driven experiment roadmap. Use when the user asks for a detailed experiment plan, ablation matrix, evaluation protocol, run order, compute budget, or paper-ready validation that supports the core problem, novelty, simplicity, and any LLM / VLM / Diffusion / RL-based contribution.

Prüft App-AGB auf typische Risiken, trennt Einbeziehung, Transparenz und Inhaltskontrolle, und liefert Klauselampel, Redline und Ersatzformulierungen mit gerichtsfester Begründung.

Runs throwaway experiments to validate feasibility, compare approaches, and surface unknowns before committing to a real build.

Applies the COBIT framework to design scalable, maintainable, and interoperable enterprise systems and solutions.

Install and operate Hermes Tweet, the native Hermes Agent X/Twitter plugin for endpoint discovery, read-only calls, and explicitly gated action-only workflows.

Generates comprehensive GitHub project plans with Epic > Feature > Story/Enabler > Test hierarchy, dependencies, priorities, and automated issue tracking.