An interactive Telegram skill that presents multiple clarifying questions as a structured form with inline buttons and free-text support.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install questions-form
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install questions-form using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The Questions Form skill is designed to optimize how AI agents gather information from users on Telegram. Instead of asking questions one-by-one, which can be tedious and disruptive, this skill allows the agent to present a suite of questions simultaneously. Each question is rendered as a separate message with intuitive inline buttons, allowing users to provide structured responses or utilize a free-text escape hatch for more complex answers.
This approach is essential for Openclaw Skills that require multi-faceted requirement gathering, onboarding flows, or preference collection. By utilizing a standardized callback protocol, the skill ensures that data is collected accurately and remains manageable for the agent's internal logic. This structured interaction model significantly improves user experience by providing a clear, non-linear way to complete complex input tasks within the chat interface.
To implement this within your Openclaw Skills environment, ensure your agent is configured for Telegram and follow the protocol for defining callback data. No external dependencies are required beyond a standard Telegram bot integration.
# Define your internal state and tracking logic
form_state = { "type": null, "timeline": null }
# Ensure your callback handlers look for the form: prefix
Ensure that all button callback data follows the form:<question_id>:<value> convention to maintain compatibility with the state manager.
The skill organizes data through a state object and specific callback conventions to ensure lightweight processing within the 64-byte Telegram limit.
| Component | Description | Format |
|---|---|---|
| form_state | Internal object storing user responses | Key-Value Pairs |
| callback_data | The button payload for Telegram communication | form:<qid>:<value> |
| qid | Short question identifier (2-8 chars) | String |
| value | The selected option identifier or 'other' | String |
Loading
TokenGuard is a lightweight prevention engine that intercepts LLM API requests to avoid rate limits and optimize token usage efficiency.

A streamlined utility pack designed to install curated bundles of AI agent skills in a single command.

A lightweight Python engine that orchestrates multi-agent squads by routing tasks to the most efficient model based on skill requirements and cost.

A high-efficiency financial tracking engine for AI agents to monitor API costs, gas fees, and revenue in real-time.

An AI-powered medical assistant providing educational insights into symptoms, diseases, medications, and general health maintenance.

A specialized AI agent for fundamental and technical investment analysis across stocks, FIIs, and ETFs.








































