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context-builder

Generate interactive AI transformation context-builder prompts for consulting clients. Use when creating structured discovery session prompts that g…

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技能内容

Context Builder

Generate interactive context-building prompts for consulting clients. These prompts are designed to be run in Claude Code -- they guide a team through structured questions using AskUserQuestion, generate output files per section, and compile everything into a reusable CLAUDE.md.

Workflow

Phase 1: Intake (AskUserQuestion)

Ask all intake questions using AskUserQuestion with closed-list options. Gather:

Question 1: Company identifier

  • Options: "I have a website URL", "I have a company name", "I have both"
  • Follow up to get the actual URL/name

Question 2: Who will use this prompt?

  • Options: "Specific person (name + role)", "A team (no specific person)", "Unknown / TBD"
  • If specific person: follow up for name and role

Question 3: Primary consulting focus (multiSelect)

  • "AI automation of current operations"
  • "Existential strategy (what survives AI)"
  • "New business models / pivots"
  • "Product development with AI"

Question 4: Industry

  • "Marketing / Advertising"
  • "Manufacturing / Construction"
  • "SaaS / Software"
  • "Professional Services / Consulting"
  • (Other)

Question 5: Existing context in vault?

  • "Yes, there's a call transcript"
  • "Yes, there are notes/files"
  • "No existing context"
  • If yes: ask for filename or search term to locate it

Question 6: Session language

  • "Russian (questions in Russian, output in English)"
  • "English throughout"
  • "Other"

Phase 2: Research (automated)

Run these research steps in parallel where possible:

  1. Web research: Use WebSearch and WebFetch (via Task agent) to gather:
  • What the company does, products/services
  • Target market, company size, geography
  • Tech stack, partnerships
  • Recent news, funding, team info
  • Competitive landscape
  1. Vault search: Search the Obsidian vault for:
  • Transcripts mentioning the company name (Grep in vault root and Daily/)
  • People files for contacts at the company (People/ folder)
  • Any existing notes or research
  1. Transcript analysis (if found): Extract from call transcripts:
  • Team members and their roles
  • Current AI tool usage
  • Pain points and concerns mentioned
  • Specific processes described
  • Questions raised by the team

Phase 3: Section Selection (AskUserQuestion)

Present a curated set of sections based on the consulting focus. Use AskUserQuestion with multiSelect to let the user pick which sections to include.

Section Library

Draw from references/section-library.md for the full section catalog. Default section sets by focus:

AI Automation focus:

  1. Process Inventory, 2. Pain Points & Waste, 3. Current Tech Stack, 4. AI Opportunity Mapping, 5. People & Org, 6. Data Reality Check, 7. Quick Wins

Existential Strategy focus:

  1. Revenue & Service Map, 2. The Existential Question, 3. Client Value Chain, 4. New Business Models, 5. Data & Knowledge Assets, 6. People & Org, 7. Quick Wins & Pilots

Full Assessment (both):

All 10 sections from the library.

After section selection, ask:

Express mode grouping: Present a suggested grouping of selected sections into 4 Express mega-sections. Let user confirm or adjust.

Phase 4: Generation

Generate two files:

1. The Context-Builder Prompt

Save to: Claude-Drafts/{company-slug}-context-prompt.md

Structure (follow the template in references/prompt-template.md):

---
created_date: '[[YYYYMMDD]]'
type: draft
topic: consulting, AI transformation, {industry}
for: {contact person or team name}
---

# AI Transformation Context Builder -- {Company Name}

## About {Company}
  [Generated from research -- company description, size, market, positioning]

## Current State
  **What's working:** [from research + transcript]
  **The gap:** [from research + transcript]
  [If existential concerns found: **Existential context:**]

## Mode Selection
  [Express vs Deep Dive with section descriptions]

## How This Works
  [Standard interactive session instructions]

## Session Resumability
  [Standard resumability logic]

## Interactive Flow
  [Selected sections with tailored questions]

## Output Files
  [One file per section + final CLAUDE.md]

## Relevant Frameworks
  [Selected from references/frameworks.md based on focus]

2. Instruction File (optional)

If the prompt will be sent to someone external, generate a short instruction file:

Claude-Drafts/{company-slug}-context-instructions.md

Containing:

  • What this file is and how to use it
  • Prerequisites (Claude Code or similar)
  • The two modes explained simply
  • What they'll get on output
  • Privacy note (they can share as much or as little as they want)

Phase 5: Delivery (AskUserQuestion)

Question: What to do with the generated files?

  • "Save to vault only"
  • "Save and send via Telegram"
  • "Save and let me review first"

If Telegram: ask for the recipient handle/name, then send using the telegram skill (intro message + file).

Key Principles

  • Maximize closed-list questions: Every AskUserQuestion should have concrete options. Minimize free-text input.
  • Research before asking: Don't ask the user things that can be found via web search or vault search.
  • Tailor sections to context: If the transcript reveals specific concerns (e.g., existential fears, specific tech stack), customize the section questions to reference those specifics.
  • Bake in discovered context: The generated prompt's "About" and "Current State" sections should be rich with researched details so the person running the prompt gets a warm start.
  • Language awareness: If session language is Russian, all AskUserQuestion interactions during prompt execution should be in Russian, but output files in English.

Resources

references/

  • section-library.md -- Full catalog of available sections with question templates
  • prompt-template.md -- Structural template for the generated prompt
  • frameworks.md -- Consulting frameworks to selectively include

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