Search Results for "actual"

...It lets users give agents defined roles, email addresses, task boards, calendars, and shared workflows so they can collaborate more like a real team. The platform connects local agents to external communication channels while keeping the actual agents and codebase running on the user’s own machine. It is designed for developers, solo founders, and teams that want multiple AI agents to handle development, operations, research, and routine work with clearer structure. Alook also emphasizes memory and traceability, so agents can remember past decisions, learn preferences, and keep a record of instructions and replies. ...

...Instead of forcing agents to repeatedly scan files with grep, glob, and read commands, it builds a searchable knowledge graph of symbols, relationships, call graphs, and code structure. The project uses deterministic parsing rather than LLM summaries, which makes its indexed data more predictable and grounded in the actual source tree. It is designed for tools such as Claude Code, Codex, Cursor, and OpenCode, with MCP support for agent access. CodeGraph stores project data locally, which helps reduce token usage and repeated file exploration. Its main purpose is to make agent-assisted coding faster, cheaper, and more context-aware.

...The repository organizes translated articles, diagrams, and examples in a way that mirrors the structure of the original codebase, helping users correlate documentation with the actual implementation. It also includes localized explanations of conceptual topics such as agent reasoning, message handling, workflow design, and best practices.

...ChatGPT can request only the workspace information, files, search results, Git status, diffs, test status, and execution records it needs. After Codex makes changes, ChatGPT can independently inspect the actual diff and test evidence before continuing the loop. The bridge uses OAuth, one-time pairing, workspace boundaries, path containment, and sensitive-file blocking to limit access. Setup and updates are designed to be largely automated through a Codex skill, with Cloudflare tunneling used to expose the local read-only bridge when needed.

...Screenshots of the mirrored window provide visual input, while Apple's Vision framework extracts visible text and tap-ready coordinates. macOS CGEvents supply taps, long presses, drags, scrolling, keyboard input, and iPhone Mirroring shortcuts. After performing an action, the agent captures the screen again to verify the actual resulting state. The harness can be installed as an agent skill for systems such as Claude Code or Codex. Its editable helper workspace also lets an agent create missing automation functions during execution.

improve is an agent skill that audits a codebase and writes implementation plans for other agents or humans to execute. Its core idea is to use a stronger model for understanding, judgment, and planning, then hand the actual implementation to cheaper or separate execution agents. The skill does not modify code by default, because its main output is a self-contained plan. It can run full, quick, deep, security-focused, branch-scoped, and feature-suggestion audits. It maps repository conventions, identifies findings, writes ordered markdown plans, and records verification steps such as lint, build, and test commands. ...

Superplan is an execution system for AI agents. It turns planning into actual execution inside your repository. Instead of vague plans, chat history, or TODO lists, Superplan forces work into clear, step-by-step tasks that agents can execute, track, and resume at any time. The CLI is designed for agents to follow, not for humans to run manually. You define the work; your agent executes it through Superplan's structured runtime.