smithery/neversight

dialog

Fast product research with Dialog. Use when the user wants to validate ideas, test concepts, or get customer feedback before building.

Installation

$ npx skills add smithery/neversight --skill dialog

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents claude-code

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 1,786 B
  • docs SUMMARY.md 148 B

History

  1. First recorded snapshot · 0 installs

SKILL.md

Dialog

Fast product research. Dialog makes direct customer insights part of the product development cycle by conducting AI-powered interviews at scale.

First: Check MCP Setup (Claude)

Check if dialog_generate is available.

If not available:

  1. Run bash: claude mcp add dialog --transport http https://api.rundialog.com/mcp
  2. Tell user: "Dialog is set up. Restart Claude Code and run /dialog again."
  3. Stop there.

Tools

  • dialog_generate - Create a study from a natural language description
  • dialog_source - Configure participant recruitment (count and criteria)
  • dialog_launch - Launch a study to start collecting responses
  • dialog_status - Check study progress (completed/active interviews)
  • dialog_analyze - Ask questions about collected interview data
  • dialog_list - List all studies in the organization
  • interview_read - Read a full interview transcript

Workflow

  1. Create: Use dialog_generate to create a study from what the user wants to learn
  2. Source: Use dialog_source to define participant criteria and count
  3. Launch: Use dialog_launch to start collecting interviews
  4. Monitor: Use dialog_status to check progress
  5. Analyze: Use dialog_analyze to extract insights

Guidelines

  • Studies typically have 3 segments with 2-4 outcomes each
  • Participants are from a general population pool (US-based by default)
  • Frame questions for average consumers, not niche experts
  • 5-10 participants is good for initial validation
  • Up to 10 participants on free tier
  • Always confirm before launching (it recruits real participants)