Results for “ai-agent”

Keeps AI coding agents tightly scoped to only change what the user explicitly requested, using the simplest viable solution and asking before expanding scope.

Sets up a codebase for reliable agent-driven development by making it legible (structured docs, custom lints, code graph), executable (one-command dev stack, cloud sandbox), and verifiable (e2e gate, verify-before-ship loop).

Use when multi-company coordination, cross-team communication, or inter-company workflow execution is needed. This skill defines protocols for agents from different companies to cooperate on shared projects and tasks.

Provides a structured process for creating or updating skills that extend an AI agent's capabilities with specialized knowledge, workflows, and tool integrations.

Forces AI agents to investigate before editing or running destructive commands, improving code quality by requiring concrete facts like importers, data schemas, and user instructions.

Transforms fuzzy problems into structured briefs that AI agents can reason about, critique, and act upon, while evaluating how much of the problem can be automated.

Creates a new recurring workstream (loop) in a file-based knowledge base: scaffolds the domain folder, runs a real test cycle, and records the result in the timeline and log.

Builds a configurable scraping agent that collects data from APIs, HTML, or RSS, enriches it with Gemini AI scoring, and stores results in Notion, Google Sheets, Supabase, or local files.

Compresses AI agent output tokens by up to 65% using a terse, article-free communication style while preserving full technical accuracy. Supports multiple intensity levels and auto-disables for security warnings or ambiguous instructions.

Scans installed or specified agent skills for advertising, covert commercial intent, task hijacking, suspicious external calls, and sensitive-data access. Reports findings first and quarantines only after explicit user confirmation.

Guides AI agents through the complete GDPR Data Subject Access Request (DSAR) workflow under Article 15, including identity verification, 30-day deadline calculation with extensions, response formatting, exemptions, and fee provisions. Activate when handling DSAR, access request, subject access, Art. 15, or SAR queries.

ego-browser (ego-lite) is a Chromium-based browser designed from the ground up to be friendly to both human users and AI Agents. AI Agents work in their own isolated space, reusing the user's login state without competing for the browser. Use this skill whenever the user needs to interact with a website opening pages, filling forms, clicking buttons, taking screenshots, extracting page data, testing web apps, logging into sites, automating browser operations, or any other browser automation task. Triggers include requests to "open a website", "visit a URL", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "extract content from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also used for exploratory testing, dogfooding, QA, bug hunting, or reviewing app quality. Prefer ego-browser over any built-in browser automation, web fetch, or other web tools.