| name | setup |
| description | Initialize a new cogni-portfolio project with company context and directory structure.
Use whenever the user mentions creating a portfolio, new portfolio project, setting up
portfolio, "start portfolio planning", "new company", "new project", or wants to begin
structuring their product/market messaging — even if they don't say "setup" explicitly.
|
Portfolio Project Setup
Initialize a cogni-portfolio project by capturing company context and creating the project directory structure.
Core Concept
A portfolio project is the container for all downstream work — products, features, markets, propositions, competitors, and customers all live inside it. Setup captures the minimum viable company context (name, description, industry, products) and scaffolds the directory structure that every other skill depends on.
Getting this right matters because the company context in portfolio.json informs every downstream skill. A clear description and accurate industry help the products, markets, and propositions skills generate relevant, on-target output instead of generic filler. A few minutes of care here saves hours of correction later.
If a project already exists for the company, redirect to the resume-portfolio skill instead of creating a duplicate.
Workflow
1. Gather Company Context
Collect four required fields:
- Company name: Legal or trading name
- Description: One-sentence summary of what the company does
- Industry: Primary industry sector (e.g., "Cloud Infrastructure", "B2B SaaS")
- Products: List of main products or services offered
If the user has provided some context already, extract what is available and ask only for missing fields.
Language detection: After collecting the four fields above, check if a .workspace-config.json file exists in the workspace root directory. If it contains a language field, lowercase the value and use it as the portfolio language (e.g., "DE" becomes "de"). If no workspace config exists or it has no language field, ask the user which language to use for generated content (default: "en").
Web research (optional): When the user provides a company URL or website, delegate to a subagent (Agent tool) to extract company description, industry, and product offerings from the company's public pages. This is especially useful when the user knows the company but hasn't articulated structured context yet. Present findings to the user for confirmation — never auto-populate without review.
2. Review with User
Present the gathered context as a summary for confirmation before creating anything:
| Field | Value |
|---|
| Company | Acme Cloud Services |
| Description | Cloud infrastructure management for mid-market SaaS |
| Industry | Cloud Infrastructure |
| Products | Cloud Platform, Monitoring Suite |
| Proposed slug | acme-cloud |
| Language | de (from workspace config) |
The slug is derived from the company name in kebab-case — keep it short and recognizable (e.g., "Acme Cloud Services" -> acme-cloud).
Ask explicitly:
- Does this look right?
- Anything to add or correct?
- Happy with the project slug?
Iterate until the user confirms. They know their business best.
3. Create Project Structure
Run the init script to create the directory structure:
bash $CLAUDE_PLUGIN_ROOT/scripts/project-init.sh "<workspace-dir>" "<project-slug>"
The workspace directory is the user's current working directory. The script creates:
cogni-portfolio/<project-slug>/
products/
features/
markets/
propositions/
solutions/
competitors/
customers/
uploads/
output/
4. Write portfolio.json
After the script creates directories, write portfolio.json in the project root with the confirmed company context, including the language field. Follow the schema in $CLAUDE_PLUGIN_ROOT/skills/setup/references/data-model.md.
5. Confirm and Guide Next Steps
Present the created project structure and suggest the full workflow. If the user has existing documents (product specs, market research, pitch decks, etc.), mention they can drop files into the uploads/ folder and run the ingest skill to import data automatically.
- (Optional) Drop existing documents into
uploads/ and run the ingest skill
- Define products with the
products skill
- Add features to each product with the
features skill
- Discover target markets with the
markets skill
- Generate proposition messaging with the
propositions skill
- Define implementation plans and pricing with the
solutions skill
- Enrich with
compete (competitor analysis) and customers (buyer profiles)
- Verify web-sourced claims with the
verify skill
- Aggregate into messaging repository with the
synthesize skill
- Generate deliverables with the
export skill
Data Model Overview
The portfolio data model has six entity types:
| Entity | Storage | Key Concept |
|---|
| Product | products/{slug}.json | Named offering that bundles features |
| Feature (IS) | features/{slug}.json | Market-independent capability (belongs to a product) |
| Market | markets/{slug}.json | Target segment with TAM/SAM/SOM |
| Proposition | propositions/{feat}--{mkt}.json | Feature x Market = DOES + MEANS |
| Solution | solutions/{feat}--{mkt}.json | Implementation plan + pricing tiers per proposition |
| Competitor | competitors/{feat}--{mkt}.json | Per-proposition competitive landscape |
| Customer | customers/{mkt}.json | Per-market ideal buyer profile |
| Claims | cogni-claims/claims.json | Web-sourced claim verification registry |
For complete entity schemas and naming conventions, consult $CLAUDE_PLUGIN_ROOT/skills/setup/references/data-model.md.
Important Notes
- Each project lives under
cogni-portfolio/<slug>/ in the workspace
- Multiple projects are supported (one per company or product line)
- If a project already exists, the init script returns
"status": "exists" without overwriting
- The
updated field in portfolio.json should be refreshed whenever entities change
- Communication Language: Read
portfolio.json in the project root (or use the language determined during setup). If a language field is present, communicate with the user in that language (status messages, instructions, recommendations, questions). Technical terms, skill names, and CLI commands remain in English. If no language field is present, default to English.
