TLDR;
This video provides an update on Cloud Code, focusing on new features designed to improve efficiency and collaboration. It covers the Tool Search feature, which optimizes context management by dynamically fetching tools instead of loading them directly into the context. The merging of slash commands into skills is discussed, streamlining command execution and context loading. The most significant update is the introduction of Tasks, a new primitive for tracking and completing complex features collaboratively across multiple sessions and sub-agents.
- Tool Search optimizes context management by dynamically fetching tools, reducing token usage.
- Slash commands are merged into skills for streamlined command execution and context loading.
- Tasks are introduced as a new primitive for collaborative feature development across multiple sessions.
Introduction [0:00]
The video introduces new features in Cloud Code, including tasks, merging slash commands into skills, and tool search, providing an update on how these tools function within the Cloud Code environment. The primary focus is on demonstrating how these updates can improve the coding experience directly in the terminal.
Présentation du tool search [0:45]
The Tool Search feature addresses the issue of excessive token usage by MCPs (Managed Context Providers) in Cloud Code. When many MCPs are loaded, they consume a significant portion of the context window, even if they are not frequently used. The Tool Search allows Cloud Code to dynamically search for available tools instead of including them in the context, reducing the initial token load.
Impact des MCP sur le contexte [2:00]
By activating the Tool Search via API, MCPs are removed from the context, and the AI is prompted to search for them when needed. This change reduces the context size, freeing up tokens. The video demonstrates how, without Tool Search, MCPs can take up a substantial portion of the context, whereas with Tool Search enabled, the context remains cleaner and more efficient.
Démo du tool search par API [4:00]
The demonstration shows how to use the Tool Search to find specific MCPs. Instead of having all MCPs loaded in the context, the AI searches for the necessary tools when prompted. The AI uses "Tool Search" to find and list available MCPs, such as web frameworks, by calling specific tools like "ExaWebSearch."
Comparaison avec et sans MCP [6:00]
A comparison is made between having MCPs directly in the context versus using the Tool Search. When MCPs are in the context, the AI readily uses them, but when Tool Search is enabled, the AI may not always utilize the available MCPs, even when they are more efficient. This can be a problem if specific MCPs are preferred for their speed and accuracy.
Désactiver l'option dans settings.json [7:45]
The video explains how to disable the Tool Search feature in the settings.json file by setting "Enable Tool Search" to false. Disabling this feature is recommended if the MCPs consume less than 2-3% of the context, ensuring that preferred MCPs are always readily available.
Fusion des commandes et des skills [8:45]
Cloud Code has merged slash commands into skills, simplifying how commands are managed. Skills are more powerful for loading context dynamically by reading files referenced in skill.md, allowing for multiple dynamic context levels. The combination streamlines Claude's understanding, eliminating the need for separate command and skill tools.
Présentation des nouvelles Task [11:30]
The most significant update is the introduction of Tasks, which replace to-dos as the new primitive for tracking and completing complex features. Tasks allow for better collaboration across sessions and sub-agents, addressing the limitations of to-dos in larger projects with multiple dependencies and coordination needs. Tasks enable the coordination of multiple work pieces and support dependencies between them.
Démonstration pratique sur une application [14:15]
The video demonstrates Tasks in a chat application, where the agent is divided into several tasks. By using the command cloudcode task listID, the AI creates a task list to fix bugs and implement new features. Each task is tracked with a specific ID and status, such as "pending" or "in progress," and can be blocked by other tasks.
Collaboration entre sessions et subagentes [17:30]
Tasks facilitate collaboration between different terminals or agents. When one agent starts a task, it is marked as "in progress," and other agents are aware of its status. This shared state allows multiple agents to work on different tasks simultaneously, ensuring that they do not duplicate efforts and can proceed to subsequent tasks once the preceding ones are completed.
Gestion des dépendances entre Task [20:00]
The demonstration illustrates how tasks can be dependent on each other. Agents can identify which tasks are blocked by others and proceed accordingly. The ultimate goal is to enable multiple agents to work on the same task list, facilitating large refactors and complex projects by distributing the workload efficiently.
Conclusion et ressources de formation [22:30]
The video concludes by highlighting the significant improvements that Tasks bring to Cloud Code, adding considerable value to the development process. The presenter encourages viewers to update their Cloud Code configurations and join the IA formation for more in-depth training and support.
