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Skill · Development

Go in depth

Go in depth harness — fan-out web searches, fetch sources, adversarially verify claims, synthesize a cited report.

Agentic Awesome SkillsAdded Sep 5, 2026

How to use it

  1. Start your plan and connect your AI once
  2. Ask for the task in your own words, or say it directly:
Use the Go in depth skill to help me with this.

Without a connection: copy the SKILL.md below into your AI's project instructions.

SKILL.md2 files in this skill

Go In Depth

Overview

Go in depth harness — fan-out web searches, fetch sources, adversarially verify claims, synthesize a cited report. Run the "go-in-depth" workflow.

When to Use

When the user wants a deep, multi-source, fact-checked research report on any topic. BEFORE invoking, check if the question is specific enough to research directly — if underspecified (e.g., "what car to buy" without budget/use-case/region), ask 2-3 clarifying questions to narrow scope. Then pass the refined question as args, weaving the answers in.

How It Works

Phases:

  • Scope: Decompose question (from args) into 5 search angles
  • Search: 5 parallel WebSearch agents, one per angle
  • Fetch: URL-dedup, fetch top 15 sources, extract falsifiable claims
  • Verify: 3-vote adversarial verification per claim (need 2/3 refutes to kill)
  • Synthesize: Merge semantic dupes, rank by confidence, cite sources

Examples

Example 1: Run go-in-depth workflow

Workflow({ name: "go-in-depth" })

Example 2: Research with refined question

Workflow({ name: "go-in-depth", args: { query: "best hybrid cars under $30k in the US for families" } })

Example 3: Deep dive into a technical concept

Workflow({ name: "go-in-depth", args: { query: "how does the transformer architecture handle positional encoding?" } })

Example 4: Fact-checking a medical claim

Workflow({ name: "go-in-depth", args: { query: "efficacy of intermittent fasting for long-term weight loss in adults" } })

Workflow Script

[scripts/workflow-script.js](scripts/workflow-script.js)

Limitations

  • Slow execution: Multi-agent searches, fetching, and 3-vote verification take significant time. Not for quick facts.
  • Context intensive: Analyzing 15 full sources uses large context limits.
  • Synthesis risks: May struggle if source material is weak or equally conflicting.