Skill: skills-airtap/airtap (version 1.0.7)

--- name: airtap description: >- Use this skill when the user wants to operate Airtap or complete a request through a mobile app on an Airtap device. It lists receivers and models, creates Airtap tasks, monitors them locally by default, sends follow-up messages, cancels tasks, updates user location, and can mirror progress updates into OpenClaw when needed. metadata: {"clawdbot":{"emoji":"📱","requires":{"bins":["python3"],"env":["AIRTAP_PERSONAL_ACCESS_TOKEN"]},"primaryEnv":"AIRTAP_PERSONAL_ACCESS_TOKEN"}} --- # Airtap Use the bundled `scripts/airtap.py` CLI to interact with Airtap tasks. ## Safety - Use this skill for Airtap or mobile-app requests that can be delegated to an Airtap device. - Prefer `--receiver-id cloud`. Do not target a physical receiver unless the user explicitly asks for that device. - `task poll` is local-only by default. Use OpenClaw delivery only when the host explicitly wants mirrored updates. - Do not ask the user to paste tokens into chat. Use preconfigured environment variables or the local `scripts/.env` file. - Never invent OpenClaw targets, thread IDs, reply IDs, or account scopes. ## Setup Run commands from the skill directory. First, sign in to `https://airtap.ai/app`, open Settings, create a personal access token, and copy it. Create or update `scripts/.env` with: ```bash python3 scripts/airtap.py --add-token "your-personal-access-token" ``` Or copy the template and fill in the personal access token: ```bash cp scripts/env.example.txt scripts/.env ``` The script loads `scripts/.env` on startup and values from that file override same-named shell environment variables. Requires `requests` and `python-dotenv`. If missing: ```bash pip3 install -r requirements.txt ``` ## Command Reference Run all commands as `python3 scripts/airtap.py <resource> <action> ...`. | Command | Use when | Notes | | --- | --- | --- | | `receiver get-list` | You need to choose a receiver. | Helpful before task creation. | | `model get-list` | Model choice matters for the task. | Main Airtap choices are `airtap-1.0` and `airtap-1.0-flash`. | | `task create` | You want to start a new task. | Add `--model-id <id>` only to override the default model. | | `task get-list` | You need recent tasks. | Useful when you need to recover a `taskId`. | | `task get-details` | You need a one-time task snapshot. | Useful for debugging or inspecting the final state. | | `task poll` | You need to monitor a running task. | Polls locally by default and can optionally forward updates into OpenClaw. | | `task add-user-message` | The task needs more input. | Use for clarification, continuation, or resuming work. | | `task cancel` | The task should stop. | Use when the user no longer wants the task to continue. | | `user update-location` | The task depends on user location. | Send the location as raw JSON. | ## Choosing A Model - Only list models when model choice matters. Do not call `model get-list` for every task. - If you do not send `modelId` during task creation, Airtap defaults to `airtap-1.0-flash`. - `Airtap 1.0 Flash` (`airtap-1.0-flash`) is the default. Use it for shorter tasks that benefit from lower latency. - `Airtap 1.0` (`airtap-1.0`) is slower. Use it for more complex tasks where better reliability is worth the extra latency. - `model get-list` returns the models available to the current account. Most users see `airtap-1.0` and `airtap-1.0-flash`. Debug users may also see `airtap-1.0-lite`. ## Monitoring Long-Running Tasks Airtap tasks can take a few seconds to several minutes. Treat them as long-running jobs. 1. Create the task and capture the returned `taskId`. 2. If you only need a local wait loop, call `python3 scripts/airtap.py task poll --task-id "<task-id>"`. 3. If the host explicitly wants OpenClaw channel updates, read `references/openclaw.md` and call `task poll` with `--openclaw-target` and any routing fields required for the destination conversation. 4. Let `task poll` keep polling until `taskState` reaches one of the states in the task-state glossary below. 5. Read the final JSON response from `task poll`. `task poll` is the main monitoring command: - It polls `task get-details` internally every 10 seconds by default. - It stops automatically when the task completes, fails, is cancelled, or needs user input. - It returns the same task details payload plus a `_poll` summary. - Bare `task poll --task-id ...` only polls Airtap locally. - OpenClaw delivery requires `--openclaw-target`. - OpenClaw delivery is milestone-based by default: acknowledgement, one plan/start update, and the final or waiting-state update. - Add `--openclaw-verbose` only when the host explicitly wants every Airtap agent update forwarded. - Detailed OpenClaw routing flags and examples live in `references/openclaw.md`. How to read the task details returned by `task poll` or `task get-details`: - `messages` is ordered conversation history. The first message is typically the original user request. Later entries are usually agent updates. - Most progress updates come from the latest `type: "agent"` message. - Inside an agent message, inspect text parts first. - `text` is the main progress update. - `group` and `subGroup` are UI grouping fields that help categorize the update. - `queuedUserMessages` may contain user follow-ups that have been accepted but not processed yet. ## Task States - `COMPLETED`: the task finished successfully. - `FAILED`: the task could not be completed. - `CANCELLED`: the task was cancelled. - `WAITING_FOR_USER_INTERVENTION`: the user must perform some action on the device. - `WAITING_FOR_USER_INPUT`: the agent needs clarification before continuing the task. - `WAITING_FOR_USER_CONTINUE`: the task reached the maximum step limit and needs approval to keep going. ## Required Agent Behavior - If the host expects OpenClaw channel updates while Airtap is running, call `task poll` with `--openclaw-target` and the required routing flags. Otherwise use local-only `task poll`. - Use milestone-only OpenClaw delivery by default. Add `--openclaw-verbose` only when the host explicitly wants every Airtap step forwarded. - On `WAITING_FOR_USER_INPUT`, ask the user the needed clarification, then forward the answer with `task add-user-message`. - On `WAITING_FOR_USER_INTERVENTION`, tell the user exactly what action they need to perform on the device, wait for confirmation, then resume with `task add-user-message`. - On `WAITING_FOR_USER_CONTINUE`, summarize the progress so far, ask whether to continue, and if the user approves, resume with `task add-user-message`. - On `COMPLETED`, summarize the result using the latest agent updates. - On `FAILED` or `CANCELLED`, report the final state and any useful context from the latest agent message. - If any Airtap API call returns `404` or another request failure, tell the user to get an updated version of the Airtap skill before retrying. ## Examples Create a task with the default model: ```bash python3 scripts/airtap.py task create --message "Open Instagram" --receiver-id cloud ``` List available models when the task is complex: ```bash python3 scripts/airtap.py model get-list ``` Create a task with the more reliable Airtap model: ```bash python3 scripts/airtap.py task create \ --message "Compare the price of a product on Amazon and Zepto" \ --receiver-id cloud \ --model-id airtap-1.0 ``` Monitor a running task locally only: ```bash python3 scripts/airtap.py task poll --task-id "task_abc123" ``` Answer a clarification request or continue a paused task: ```bash python3 scripts/airtap.py task add-user-message --task-id "task_abc123" --message "Continue" ``` Cancel a task: ```bash python3 scripts/airtap.py task cancel --task-id "task_abc123" ``` ## Notes - Image attachments are supported for `task create` and `task add-user-message` via `--image-file`. - For OpenClaw relay details and examples, read `references/openclaw.md`.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)