From web_search_xray
Run broad, parallel web searches with diverse query variants, then aggregate and synthesize findings into a concise report with traceable sources.
How this skill is triggered — by the user, by Claude, or both
Slash command
/web_search_xray:web_search_xrayThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
`web_search_xray` is built from the same core workflow as `maratha_web_search`: generate diverse queries, search in parallel, deduplicate results, deep dive into the strongest sources, and produce a concise report with citations.
web_search_xray is built from the same core workflow as maratha_web_search: generate diverse queries, search in parallel, deduplicate results, deep dive into the strongest sources, and produce a concise report with citations.
The difference is that web_search_xray adds a stricter evidence pass: it explicitly ranks sources by authority, recency, and directness so the final answer is easier to audit.
Analyze the user's topic and craft 5-10 diverse search queries approaching it from different angles:
2026, latest, recent) where relevantsite:github.com, research paper, official docs, tutorial, comparison, vs, benchmark as appropriatehow to, what is, why does, best practices forinternals, architecture, implementation, deep diveStart with at least 5 queries. For ambiguous or fast-moving topics, use 8-10.
If the broad-query pass is noisy, ambiguous, or too shallow, switch into an operator-driven search pass.
Use this mode when you need to:
arxiv.orgUse the following operators when the search engine supports them:
"exact phrase": exact-match a phraseOR or |: allow alternativesAND: require both terms-term: exclude a term or phrase*: wildcard within a phrase( ... ): group alternativessite:: restrict to a domain or sitefiletype: or ext:: restrict to file types such as pdfintitle:: require a term in the titleallintitle:: require multiple title termsinurl:: require a term in the URLallinurl:: require multiple URL termsintext:: require a term in the body textallintext:: require multiple body termsbefore:: restrict to results before a dateafter:: restrict to results after a daterelated:: find related domainsdefine:: definition lookupUse with caution because support can be inconsistent:
AROUND(X): proximity search#..#: numeric range searchsource:: news-source targetingAvoid relying on deprecated or weak operators unless you have a concrete reason and verified they still work in your target engine.
Use site:arxiv.org first, then tighten with title, URL, phrase, and time filters.
Examples:
"reward hacking" site:arxiv.org"mixture of experts" site:arxiv.org after:2024-01-01site:arxiv.org (abs OR pdf) "instruction following"site:arxiv.org inurl:abs "reinforcement learning with verifiable rewards"site:arxiv.org intitle:"reward hacking"site:arxiv.org filetype:pdf "transformer scaling"For known paper IDs, search exact identifiers:
site:arxiv.org "2508.04632"site:arxiv.org "2602.17004"Use site:, intitle:, inurl:, phrase matching, and exclusions together.
Examples:
"reward hacking" (blog OR post OR essay)intitle:"reward hacking" (blog OR essay)inurl:blog "mixture of experts"(site:substack.com OR site:medium.com) "instruction following"(site:blog.google OR site:openai.com OR site:anthropic.com) "reinforcement learning""search operators" -site:ahrefs.comExamples:
"X API" (docs OR reference OR quickstart)site:docs.x.com "follows" after:2024-01-01"reward model" filetype:pdf"Mixture of Experts" (tutorial OR guide OR benchmark)intitle:benchmark "long context" LLM(changelog OR release notes) "vLLM"Generate a query pack with one broad, one constrained, and one exclusion variant:
"topic""topic" site:example.com OR site:example.org"topic" -reddit -pinterest -linkedinsite: early when the user already has a likely source domain.after: and before: for unstable topics, releases, APIs, laws, benchmarks, and news.filetype:pdf for papers, reports, whitepapers, and slide decks.intitle: and inurl: when topical matching in the snippet is too weak.-term aggressively to remove SEO spam, mirrors, aggregators, and irrelevant brands.Send all queries as parallel web-search tool calls in a single message. Do not run them sequentially.
Once all searches return:
Before opening pages, label candidates as:
Open Primary sources first unless they are clearly stale or off-topic.
Use page-fetching or page-open tools on the most promising results. Prioritize:
During deep dives:
Before writing the response, check:
Structure findings as follows:
When appropriate, add a short Evidence Quality line explaining whether the answer is based on official docs, papers, benchmarks, or community reports.
Creates, edits, and optimizes skills for Claude Code, including drafting, evaluating with test prompts, iterating on performance, and improving skill descriptions for better triggering accuracy.
npx claudepluginhub marathan24/web_search_xray --plugin web_search_xray