Agent skill · vasilyu1983
ai-deep-research
Builds repeatable deep-research workflows for verified synthesis. Use when producing evidence-backed briefs, comparisons, dossiers, or research pipelines.
What it needs
About 10k tokens when loaded.
What this skill does
Deep Research Use this skill to design and run repeatable research workflows that gather evidence across many sources, preserve provenance, and synthesize results into decision-ready outputs. This skill covers both native deep-research agents (ChatGPT Deep Research, Gemini Deep Research, Perplexity Deep Research, Claude with web search) and custom agentic research pipelines (planner / searcher / verifier / synthesizer split). ASCII Flow Quick Reference Question Default ---------- --------- When to use a native agent vs custom pipeline? Native for ad-hoc, open-ended questions. Custom for repeatable, auditable, or multi-source workflows. What is the first artifact of any research task? The source ledger — never the synthesis. When is a source trustworthy? When it is a primary document with a stable URL, author attribution, and a verifiable date. What stops an unbounded research loop? An explicit stop criterion defined before the loop starts (saturation condition or max iterations). How to handle contradictory sources? Separate them into evidence tiers; do not resolve by averaging. Use This Skill When You need to produce a sourced comparison, brief, memo, or research dossier. You need to choose between a native deep-research agent and a custom pipeline. You want to build a repeatable, auditable research workflow with provenance. You need to detect hostile sources, citation laundering, or model-output-as-source. You need to run a verifier subagent that has not seen the researcher's context. Do Not Use This Skill For Single-lookup current facts — use ordinary browsing or direct tools. Long-lived retrieval serving — use ai-rag. Local note-vault packaging — use docs-notes-retrieval. Current Stance The durable pattern is not "send a single query and summarize the top results." The default architecture (as of lastvalidated date above): 1. Plan before searching: emit a structured research plan with queries, source targets, and success criteria before any tool call. 2. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills vasilyu1983/ai-deep-research