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channel-research-deployment

Deploy interviews, surveys, and diary studies via messaging channels (Telegram, Slack, WhatsApp, Google Chat) with adaptive questioning and real-time analytics.

Skill by henrique-simoes

IndexedMIT★ 16
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/henrique-simoes-channel-research-deployment

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About

Deploy interviews, surveys, and diary studies via messaging channels (Telegram, Slack, WhatsApp, Google Chat) with adaptive questioning and real-time analytics.

Use cases: devops, data, research, productivity

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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/channel-research-deployment

What's inside

Skill name
channel-research-deployment
Description
Deploy interviews, surveys, and diary studies via messaging channels (Telegram, Slack, WhatsApp, Google Chat) with adaptive questioning and real-time analytics.
License
MIT
Instructions
53 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# Channel Research Deployment

## Capabilities

- Deploy research studies across Telegram, Slack, WhatsApp, and Google Chat
- Adaptive questioning with LLM-powered follow-up probes
- Real-time analytics dashboard (response rate, completion rate, per-question stats)
- Automatic nugget extraction from participant responses into the Atomic Research chain
- Conversation state machine: intro, questions, probing, wrap-up
- Configurable rate limiting between questions
- LLM-judged saturation detection to avoid over-probing
- Cross-deployment overview with progress tracking

## Workflow

1. **Plan** -- Define research goals, generate question set with adaptive rules
2. **Configure** -- Set up channel instances and link to a project
3. **Deploy** -- Create and activate a deployment across selected channels
4. **Collect** -- Participants respond via messaging; adaptive probing deepens insights
5. **Monitor** -- Real-time analytics show progress, response rates, and per-question stats
6. **Analyze** -- Complete the deployment; synthesize findings into nuggets, insights, recommendations

## Input

- Research goals and questions (text or generated via plan)
- Channel instance IDs (configured Telegram/Slack/WhatsApp/Google Chat connections)
- Deployment configuration (adaptive rules, rate limits, intro/outro messages)
- Project context (auto-loaded from context layers)

## Output

- Deployment plan with question set and adaptive rules (JSON)
- Real-time analytics (response rate, completion rate, per-question breakdown)
- Nuggets with source attribution (participant, channel, deployment)
- Insights and recommendations synthesized from responses
- Full conversation transcripts per participant

## Deployment Types

- **Interview** -- Semi-structured conversational interview via messaging
- **Survey** -- Structured question set with optional branching
- **Diary Study** -- Longitudinal prompts sent on a schedule over days/weeks

## Best Practices

- 5-15 questions per interview deployment; 3-5 for diary studies
- Enable adaptive probing for interviews to capture deeper insights
- Set rate limits (30-60s between questions) to avoid overwhelming participants
- Use the intro message to set expectations and build trust
- Monitor per-question skip rates to identify confusing questions
- Complete deployments promptly to avoid participant fatigue

From henrique-simoes/Istara, MIT.

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Signals

Stars
16
Forks
5
Open issues
15
Last commit (this folder)
Mar 30, 2026 (7 months ago)
Last release
Sep 27, 2026 (1 month ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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Cite this page

channel-research-deployment skill. Agent Mart. https://agentmart.dev/skills/henrique-simoes-channel-research-deployment (last updated 2026-10-24)