Install any skill in seconds. Free to start, no credit card required.
Get Started Free →omnigent-ai/deep-research
Research checklist and source-quality guidance for the archer e2e fixture.
Passed 5 of 11 test cases with the skill, and 7 of 11 without it.
1 fixed10 passed either way7 still failing7 broke
Tokens, turns and time describe resource use, not a dollar price.
A test case the skill fixed. Same model, same prompt, with and without the skill.
During research on hydrogen fuel cell efficiency, you receive 20 search results for a sub-topic. How many top results should be fetched and read per sub-query?
| Checked | Without skill | With skill |
|---|---|---|
| Selects 2 to 3 results per sub-query for full fetching. | Missed | Passed |
The instructions your model reads when the skill loads.
Use this for any question that needs current, verifiable information from the web. The deliverable is a synthesized answer where every load-bearing claim is backed by a source you actually read.
search_web_pages(query, [site], [published_after], [published_before], [mode])
— discover candidate sources. Write the query as a natural-language
description of the ideal page, not keywords. Use mode: pro (default).fetch_page_content(url, [max_chars]) — read the full page (markdown). A
search snippet is NEVER sufficient evidence — fetch before you cite.search_web_pages per sub-query. Prefer primary sources;
use published_after for anything time-sensitive.fetch_page_content on the 2-3 most promising results per
sub-query. Quote/cite only what you read, not what a snippet implied.Sources list of the URLs you actually fetched.test cases passed, vs 7 / 11 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.