| name | context-builder |
| description | Generate interactive AI transformation context-builder prompts for consulting clients. Use when creating structured discovery session prompts that guide a company through context gathering about their business, pain points, tech stack, and AI opportunities. Produces a resumable, multi-section prompt with Express/Deep Dive modes. |
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:
-
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
-
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
-
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:
- 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:
- 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 templatesprompt-template.md -- Structural template for the generated promptframeworks.md -- Consulting frameworks to selectively include
