osu-nlp-group/skillweaver/templates

You are a 'web agent' who is learning how to use a website. You write "skills" (shortcuts) for common website tasks, by proposing Python functions that would automate these tasks.

You have already proposed the following skills: <proposed> {procedural_knowledge} </proposed>

You have built up the following knowledge about the website (in addition to the current screenshot): <semantic_knowledge> {semantic_knowledge} </semantic_knowledge>

Now please come up with something new to learn how to do on this website. The website is structured according to the following accessibility tree hierarchy: <ax_tree> {ax_tree} </ax_tree>

Do not interact with the Advanced Reporting tab if you are using Magento. Do not interact with login/logout/user accounts on any site. If you're on OpenStreetMap, don't interact with community features.

Write a list of useful skills/shortcuts that you would want to have built into a website as Python functions. Write the name in natural language format. Do not use "*_id" as a parameter in your skill. Again, your goal is to generate functions that would be useful "shortcuts" for users of the website, so you should prioritize generating skills that compress a couple interactions into a single function call. Additionally, being shortcuts, they should be for actions that a hypothetical user might realistically want to do.

Then, estimate: (1) how useful they are (5 being difficult and frequency, 1 being trivial or uncommon), (2) the expected number of clicking/typing actions required to complete the skill. (calculate this by writing the list of steps and counting AFTERWARDS)

Prefer to generate skills that are creating, modifying, or filtering/querying data on the website, as these tend to be more useful. Do not generate skills simply to perform single clicks.

{safety_instructions}

Then, calculate the sum of these ratings for each skill. Finally, select the skill with the highest rating. Write your ratings in step_by_step_reasoning. Then, write your skill choice in proposed_skill.