--- name: alfworld-task-verifier description: Use when the agent needs to check whether an ALFWorld task objective has been met after completing a sub-action (e.g., placing an object). This skill parses the task goal, evaluates the latest environment observation, and outputs a verification decision — task complete, task incomplete, or action ineffective — to guide the next step. --- # Skill: Task Verifier for ALFWorld ## When to Use Trigger this skill when: 1. The agent has just completed a key sub-action (e.g., `put {obj} in/on {recep}`) 2. The agent needs to determine whether the overall task goal is satisfied 3. The agent must decide whether to continue searching or conclude the task ## Core Workflow ### 1. Parse the Task Goal Extract from the original task description: - **Target object(s)**: What needs to be found/placed (including quantity) - **Target receptacle**: Where objects must end up - **Required transformations**: Any cleaning, heating, or cooling steps ### 2. Analyze the Observation Evaluate the most recent `Observation:` text from the environment: - Look for evidence that required objects are present in the target receptacle - Count how many target objects have been successfully placed - Note: Other items in the receptacle do not invalidate success ### 3. Make a Verification Decision | Condition | Decision | Output | |-----------|----------|--------| | All required objects confirmed in target receptacle | Complete | `Verification: Task complete. No further action needed.` | | Some but not all objects placed | Incomplete | `Verification: Task incomplete. Continue searching for {missing object(s)}.` | | Observation says "Nothing happened" | Ineffective | `Verification: Last action was ineffective. Re-assess and try a different approach.` | | Object placed in wrong receptacle | Incorrect | `Verification: Object placed in wrong location. Retrieve and redirect to {correct receptacle}.` | ### 4. Output Format Output **only** the verification decision. Do not output the next action. This skill informs the planning for the next step, not the execution. ## Example **Task:** "Find two pen and put them in garbagecan." ``` Action: put pen 3 in/on garbagecan 1 Observation: You put the pen 3 in/on the garbagecan 1. > Verification: Task incomplete. Continue searching for pen (1 of 2 placed). Action: put pen 1 in/on garbagecan 1 Observation: You put the pen 1 in/on the garbagecan 1. > Verification: Task complete. No further action needed. ``` **Example — Failed action:** ``` Action: put pen 3 in/on garbagecan 1 Observation: Nothing happened. > Verification: Last action was ineffective. Re-assess and try a different approach. ``` ## Error Handling - **Ambiguous observation**: If the observation does not clearly confirm or deny placement, navigate to the target receptacle and re-examine it to get an updated state. - **Quantity tracking**: For multi-object tasks, maintain a running count. Re-examine the target receptacle if the count is uncertain.