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From deep-research
Indexes deep research principle skills for methodology, source evaluation, hallucination prevention, and synthesis-reporting; provides /research command for orchestrated multi-agent web research with verification.
npx claudepluginhub oborchers/fractional-cto --plugin deep-researchHow this skill is triggered — by the user, by Claude, or both
Slash command
/deep-research:using-deep-researchThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Structured deep research transforms ad-hoc web searches into a repeatable, hallucination-resistant research pipeline. Without deliberate structure, research agents gravitate toward the first sources found, fail to verify claims, and produce confident reports built on unreliable foundations.
Conducts AI-powered deep research on any topic via triggers like '/deep-research [topic]' or 'deep research on [topic]'. Uses interactive AskUserQuestion for focus, output, and audience selection.
Executes multi-agent research pipeline on any topic with Scout, Investigators, Deep Diver, Verifier, Synthesizer, and Critic reviews to produce verified, sourced reports.
Runs structured multi-step web research with source synthesis, citations, skeptical evaluation, and confidence/gap analysis. Supports native and dense/frontier modes.
Share bugs, ideas, or general feedback.
Structured deep research transforms ad-hoc web searches into a repeatable, hallucination-resistant research pipeline. Without deliberate structure, research agents gravitate toward the first sources found, fail to verify claims, and produce confident reports built on unreliable foundations.
This plugin provides 4 methodology skills and the /research command for orchestrated multi-agent research sessions.
Use the Skill tool to invoke any skill by name. When invoked, follow the skill's guidance directly.
| Skill | Triggers On |
|---|---|
deep-research:research-methodology | Starting any research task — query analysis, decomposition strategies, effort scaling, dynamic replanning, stopping criteria |
deep-research:source-evaluation | Evaluating sources — credibility ranking (T1-T6 tiers), multi-provider search strategy, SEO spam detection, domain-specific source selection |
deep-research:hallucination-prevention | Any research output — hallucination taxonomy, citation verification rules, circuit breaker patterns, confidence scoring, cascading prevention |
deep-research:synthesis-and-reporting | Combining findings — deduplication, conflict resolution, narrative construction, citation formatting, report quality assessment |
Invoke a skill when there is even a small chance the work touches one of these areas:
research-methodology to plan decomposition and effort scalingsource-evaluation to assess what you findhallucination-prevention to verify before statingsynthesis-and-reporting to merge and cite properlyFor full orchestrated research sessions, use /research. The command:
research-worker agents (Sonnet) — each writes findings with a Verifiable Claims Tableresearch-verifier agents (Sonnet) — each re-fetches sources and checks claims independentlyresearch-synthesizer agent (Opus) — applies corrections, merges findings, writes final document with Confidence AssessmentAll research skills rest on three foundations:
Every claim needs a source — No unsourced assertions. If it cannot be cited, it cannot be stated as fact. Flag uncertainty explicitly.
Source quality determines output quality — 57% of research errors originate in early retrieval. Front-load high-quality sources. Prefer primary sources (T1-T2) over secondary sources.
Verify before synthesizing — Treat each agent's output as untrusted input. Cross-reference claims between sources. Use deterministic validation where possible.