Guidelines to create/update a new mode for PostHog AI agent. Modes are a way to limit what tools, prompts, and prompt injections are applied and under what conditions. Achieve better results using your plan mode.
npx skills add https://github.com/PostHog/posthog --skill implementing-agent-modes
Use the steps below to plan or implement a new mode. A mode is a way to manage the context of the agent and inject tools, prompts, and mode-related behavior relevant to a product, use case, JTBD, etc. The agent has the switch_mode tool that allows it to switch itself to another mode, which might change tools, prompt, and executables, preserving the current context. Some previously created tools are contextual, meaning they're injected on particular pages of the frontend. The modes change the approach and always have tools in the mode context.
Explore the ee/hogai/core/agent_modes/presets directory and check if there are already modes that match the user's intent. If you want to create a new mode, you should scope it by a PostHog product (Product analytics), product area (SQL), or agent (Instrumentation agent).
Add a new AgentMode to frontend/src/queries/schema/schema-assistant-messages.ts and regenerate the schema using:
hogli build:schema
Alternatively, you may use this command:
pnpm run schema:build
A mode should typically contain at least two things:
Note: you should only create new executables if the user needs to modify the prompt, behavior of that mode, or the execution loop itself.
Relevant tools might be located in ee/hogai/tools or products/<product_name>/backend/max_tools. There is a set of tools that is always injected into the context, like the read_data tool, but all other tools should be specific to the mode.
Before adding a tool to the toolkit, determine if those tools have tool dependencies. If there are dependencies (like an experiment depends on feature flag creation), loop back to the user to determine whether they want to merge modes into a single one. If they don't want to do that, make sure that you later add a trajectory example clearly explaining mode switching and tool selection.
You should also verify that the tools are backend-first. If tools apply frontend changes without passing proper context back to the conversation, you should propose a way to make them backend-first so the agent has the right context.
If the new mode contains new Django models, you should review whether the read_data, search, and list_data tools have the functionality to retrieve the models. If they don't support these models, you should use or implement one of the context providers available in ee/hogai/context/....
Update the AgentToolkit to include trajectory examples. These should be JTBD-style examples showing how the agent should achieve typical tasks with the available tools. Check the Product analytics preset for reference.
Update max-constants.tsx to include new tools and add the mode to the mode selector. You might also need to create new UI elements for displaying data from the tools.
Say you've updated the Error tracking tool to list issues. It used to be a frontend tool that only updated filters, but now it outputs error tracking issues. While the agent has the context it needs, the user also needs to see the issues in a human-readable way. In this case, you should design and implement a new component to display the tool's output.
All new modes must be feature-flagged. Example:
@property
def mode_registry(self) -> dict[AgentMode, AgentModeDefinition]:
registry = dict(DEFAULT_CHAT_AGENT_MODE_REGISTRY)
if has_error_tracking_mode_feature_flag(self._team, self._user):
registry[AgentMode.ERROR_TRACKING] = error_tracking_agent
return registry
If you have created new tools, make sure you feature flag them correctly:
You should test new tools, presets, executables, and optionally implement evals.
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
Replace with description of the skill and when Claude should use it.
Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
This skill should be used when the user wants to "create a skill", "add a skill to plugin", "write a new skill", "improve skill description", "organize skill content", or needs guidance on skill structure, progressive disclosure, or skill development best practices for Claude Code plugins.
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
Use when creating new skills, editing existing skills, or verifying skills work before deployment
Take posthog/implementing-agent-modes from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.