/Research

name: Research
version: 1.5.16
description: "Multi-agent web research with mandatory URL verification, confidence-tagged output, and four depth modes (quick to deep investigation). USE WHEN research, do research, quick research, extensive research, deep investigation, find information, investigate, extract alpha, analyze content, retrieve content, AI trends, enhance content, extract knowledge, web scraping, YouTube extraction, map landscape, competitive analysis, find it, find this, find this product, identify this, what is this, what's that thing, track down, locate, help me find, I can't find X online, can't find it online, source this — never substitute raw WebSearch/WebFetch for a multi-source find/identify/investigate request. NOT FOR people/company/entity deep background, academic papers (use ArXiv), JSON entity extraction, or content-adaptive wisdom extraction (use ExtractWisdom)."
context: fork
background: false

⚠️ MANDATORY TRIGGER

**When user says "research" (in any form), ALWAYS invoke this skill.**

| User Says | Action | |-----------|--------| | "research" / "do research" / "research this" | → Standard mode (3 agents: Claude + Gemini + Perplexity + cross-check) | | "quick research" / "minor research" | → Quick mode (1 Perplexity agent) | | "extensive research" / "deep research" | → Extensive mode (7 explorers + 2 verifiers) | | "deep investigation" / "investigate [topic]" / "map the [X] landscape" | → Deep Investigation (iterative + verification) |

**"Research" alone = Standard mode. No exceptions.**

**Deterministic alternative (EXPERIMENTAL — not yet run in the harness):** `Workflows/research.mjs` ports Standard + Extensive into a Workflow-tool script — fixed researcher roster, single batch URL-verify, cross-checked synthesis. It is parse-verified and contract-checked but has NOT yet had a live harness run, so the prose `StandardResearch.md` / `ExtensiveResearch.md` stay the default path. Do not route real research through the `.mjs` until one smoke run lands. To do that smoke run: `Workflow({ scriptPath: "skills/Research/Workflows/research.mjs", args: { question: "<trivial test>", depth: "standard" } })`. Once it runs clean, drop this experimental caveat.

Customization

**Before executing, check for user customizations at:** `~/.claude/LIFEOS/USER/CUSTOMIZATIONS/SKILLS/Research/`

If this directory exists, load and apply any PREFERENCES.md, configurations, or resources found there. These override default behavior. If the directory does not exist, proceed with skill defaults.

🚨 MANDATORY: Voice Notification (REQUIRED BEFORE ANY ACTION)

**You MUST send this notification BEFORE doing anything else when this skill is invoked.**

1. **Send voice notification**:

   curl -s -X POST http://localhost:31337/notify \
     -H "Content-Type: application/json" \
     -d '{"message": "Running the WORKFLOWNAME workflow in the Research skill to ACTION"}' \
     > /dev/null 2>&1 &

2. **Output text notification**:

   Running the **WorkflowName** workflow in the **Research** skill to ACTION...

**This is not optional. Execute this curl command immediately upon skill invocation.**

Research Skill

What It Does

Researches a topic across multiple sources and verifies every claim before delivery. Four depth modes scale from a single fast lookup to a multi-session investigation: Quick (1 agent, ~10-15s), Standard (3 agents cross-checked, ~30-60s), Extensive (7 explorers + 2 independent verifiers, ~60-90s), and Deep Investigation (progressive iteration with a persistent vault, ~3-60min). Output is confidence-tagged: [HIGH] [MED] [LOW] [CONFLICT].

The Problem

A single AI agent doing research has two failure modes that quietly wreck the result. It hallucinates URLs — confident links that go nowhere, which destroys trust in the whole report. And it answers from one angle, so it parrots whatever the first few search results said and misses conflicts, gaps, and what real people actually thought. Recap journalism is the worst offender: ask "what did fans think of X" and a lone agent hands back promoter copy dressed as consensus. This skill runs several agents in parallel, cross-checks and independently verifies their findings, checks every URL before it ships, and routes sentiment questions to community sources first.

How It Works

Multiple agents work in parallel and their findings get reconciled. Verification runs in three layers at zero added latency: each agent self-verifies its own URLs, a synthesis step cross-checks for conflicts, and dedicated verifier agents (Extensive/Deep) check findings with no access to the explorers' reasoning. Step 0 of every workflow routes sentiment questions to community scrapers before web search, and every URL is verified before delivery — a hallucinated link is a catastrophic failure.

**Official anchor (drift check):** this skill's orchestrator-worker shape matches Anthropic's published architecture — [How we built our multi-agent research system](https://www.anthropic.com/engineering/built-multi-agent-research-system) (2025-06-13). When changing the orchestration itself (rosters, verifier layers, the `.mjs` ports — not on routine research runs), re-fetch that post and compare: it names lessons we may not have adopted yet (e.g. async agent coordination). Advisory only — report divergence, never auto-adopt; an unreachable URL never blocks anything.

MANDATORY: URL Verification

**READ:** `UrlVerificationProtocol.md` - Every URL must be verified before delivery.

Research agents hallucinate URLs. A single broken link is a catastrophic failure.

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MANDATORY: Source Routing (Step 0 of every workflow)

**READ:** `SourceRoutingProtocol.md` — sentiment-signal detection + scraper-first paths for Reddit / YouTube / X / TikTok.

**The rule:** web search answers "what was published about X." Community scrapers answer "what people said about X." If the question is about fan sentiment, ratings, rea