| name | imperium-brain |
| description | The Ultimate Startup OS for Claude Code. Routes to 18 domain skills across startup ops, competitive research, and content creation. Use when the user mentions anything related to: startups, strategy, fundraising, marketing, sales, product, finance, legal, engineering, competitive research, ecosystem mapping, LinkedIn posts, carousels, presentations, slides, brand identity, tone of voice, SOPs, runbooks, video creation, API discovery, images, visual media, stock photos, or any business/startup/content topic. |
| user-invocable | false |
Imperium Brain — Startup Operating System
18 skills, 8 agents, 20 commands. Complete startup intelligence + content creation.
ROUTING TABLE
Read the user prompt. Match keywords to ONE skill (max 2 if cross-domain). Load ONLY the matched skill — never load all skills at once.
STARTUP OPS (9 skills — unchanged)
| Keywords | Skill |
|---|
| CEO, strategy, vision, board, pivot, stakeholder, fundraising, pitch deck, investor, raise, round, valuation, term sheet | skills/ceo-advisor |
| CTO, architecture, tech stack, build vs buy, tech debt, scaling, infrastructure, system design | skills/cto-advisor |
| product, PRD, roadmap, prioritize, RICE, ICE, feature, backlog, user story, MVP, discovery | skills/product-manager |
| marketing, SEO, content strategy, copywriting, landing page, email sequence, social media, growth, CRO, positioning, ads | skills/marketing |
| sales, cold email, outbound, pipeline, leads, GTM, go-to-market, negotiation, B2B, prospecting, triggers | skills/sales-gtm |
| finance, metrics, MRR, ARR, CAC, LTV, churn, runway, burn rate, financial model, unit economics | skills/finance |
| founder, validate idea, Mom Test, interviews, competitor analysis, persona, imposter, mindset, knowledge base | skills/founder |
| legal, entity, LLC, incorporation, contracts, NDA, compliance, IP, trademark | skills/legal |
| engineering, agent design, RAG, MCP, API design, CI/CD, advanced architecture | skills/engineering-advanced |
RESEARCH & INTELLIGENCE (2 skills — new)
| Keywords | Skill |
|---|
| research, competitors, competitive analysis, ecosystem, gap analysis, market map, landscape, alternatives, who else, sentiment, demo videos, feature matrix, pricing benchmark | skills/research |
| hidden API, discover APIs, endpoint, SPA, intercept, XHR, fetch requests, websocket, internal API, reverse engineer API | skills/api-discovery |
CONTENT CREATION (6 skills — new)
Rule: Before generating ANY content, check if brand/brand.json exists. If yes, read brand/brand.json + brand/tone-of-voice.md and apply brand colors, fonts, and voice. If no, use sensible defaults and suggest running /imperium:create-brand.
| Keywords | Skill |
|---|
| brand, brand identity, voice, tone of voice, colors, fonts, visual identity, brand guide, brand system | skills/brand-voice |
| LinkedIn, LinkedIn post, viral post, hook, engagement, thought leadership, personal brand, LinkedIn algorithm | skills/linkedin |
| carousel, PPTX, PowerPoint, deck, pitch deck design, slide deck, presentation slides | skills/carousel |
| video, MP4, Remotion, demo video, explainer, social clip, video content, animation | skills/video |
| HTML slides, web presentation, reveal.js, browser slides, keynote alternative | skills/slides |
| SOP, runbook, playbook, checklist, process document, standard operating procedure, workflow doc | skills/sop |
| image, images, photo, find images, find visuals, stock photo, stock video, b-roll, visual media, pictures | skills/visual-media |
ROUTING RULES
- Max 2 skills per request. If a query spans 3+ domains, ask the user to narrow focus.
- Brand context is lightweight. When loading for content skills, brand.json adds ~150 tokens. Always load it.
- Multi-skill requests: Follow the PROMPT ANALYSIS PROTOCOL below to detect explicit and implicit multi-skill needs.
- Startup ops routing is unchanged. All 9 existing skills work exactly as before.
- Never load skill body until routing is decided. Read the frontmatter/description first.
PROMPT ANALYSIS PROTOCOL
5-step protocol for detecting explicit AND implicit multi-skill needs. Replaces static keyword matching with intelligent intent analysis.
Step 1: Extract Explicit Intents
Scan the user prompt for direct keyword matches against the ROUTING TABLE above.
- Match keywords → candidate skill(s)
- Fast path: If exactly 1 skill matches AND Step 2 finds zero implicit signals → route immediately. No further analysis needed. This handles ~90% of requests.
Step 2: Detect Implicit Intents
Even when the user names only one deliverable, certain language signals reveal hidden prerequisites. Scan for these patterns:
Data signals → research prerequisite needed:
- "data-driven", "backed by data", "with stats", "with numbers"
- "based on market", "based on competitors", "how we stack up"
- "gaps in the market", "whitespace", "underserved"
- "differentiator", "unique angle", "what makes us different"
- "landscape", "who else is doing this", "market overview"
Brand signals → brand prerequisite needed:
- "on-brand", "in our voice", "our tone", "brand-consistent"
- "our colors", "matching our identity", "our style"
- "brand guidelines", "visual identity"
Strategy signals → ceo-advisor prerequisite needed:
- "should we", "what direction", "how to position ourselves"
- "moat", "defensibility", "strategic advantage"
- "where to play", "how to win", "our positioning"
Temporal signals → sequential execution:
- "then", "after that", "based on findings", "once we have", "from the results"
Parallel signals → concurrent execution:
- "and also", "plus create", "across all channels", "simultaneously"
Visual signals → visual-media prerequisite needed:
- "with images", "add photos", "find images for", "include visuals"
- "with screenshots", "product images", "stock photos"
- Content request + carousel plan includes image layouts
Step 3: Check Existing State
Before adding prerequisite skills, check what already exists in the filesystem:
-
Brand check: Does brand/brand.json exist?
- YES → use existing brand, do NOT add brand-voice as prerequisite
- NO + brand signals detected → inform user, suggest
/imperium:create-brand as prerequisite
-
Research check: Do research output files exist in cwd? (ecosystem-map.md, gap-analysis.md, competitive-*.md, market-*.md)
- YES → use existing research files as input, do NOT re-run research
- NO + data signals detected → inform user, add research as prerequisite
-
Neither exists + signals detected: Tell the user what prerequisite is needed and why, then suggest the execution plan.
Step 4: Resolve Dependencies
When multiple skills are identified, resolve execution order using the dependency graph:
Dependencies (must run sequentially):
research → content (any content skill needs research data first)
brand-voice → content (brand must exist before content applies it)
research → ceo-advisor (strategy needs market data)
research → sales-gtm / marketing (GTM needs market intelligence)
Parallel-safe combinations (same dependency level):
linkedin + carousel (both consume same research/brand inputs)
sales-gtm + marketing (both consume same research inputs)
slides + sop (independent content outputs)
Execution order: Prerequisites first → then primary skill(s), parallel where safe.
Step 5: Confirm if Multi-Step
Choose the right confirmation level based on what was detected:
| Scenario | Action |
|---|
| 1 skill, no implicit signals | Route immediately — no confirmation needed |
| 2 skills, both explicitly stated | Brief plan statement ("I'll research first, then create the post"), then execute |
| 2+ skills, any were inferred from implicit signals | Ask user to confirm before executing ("I noticed you want data-driven content — should I run research first?") |
| Ambiguous — could be 1 or 2 skills | Ask user to clarify intent |
Quick Reference: Common Implicit Patterns
| User says | They need | Why |
|---|
| "write a data-driven LinkedIn post about our market" | research → linkedin | "data-driven" + "our market" = data signals |
| "create an on-brand carousel about competitors" | brand-voice → research → carousel | "on-brand" = brand signal, "competitors" = data signal |
| "position ourselves uniquely in the market" | research → ceo-advisor | "position" + "market" = strategy + data signals |
| "write a post about what makes us different" | research → linkedin | "what makes us different" = data signal (differentiator) |
| "create content across all channels" | linkedin + carousel + slides (parallel) | "across all channels" = parallel signal |
| "should we pivot based on competitor moves" | research → ceo-advisor | "should we" = strategy signal, "competitor" = data signal |
AGENT COMPOSITION
When to use single vs multi-agent
- Single agent: User request maps cleanly to one domain (e.g., "write a LinkedIn post", "research competitors")
- Multi-agent: User request spans two domains with clear dependency (e.g., "research competitors then create content from findings")
- Max 2 agents per request — same as max 2 skills. If 3+ agents needed, break into sequential requests.
Sequential execution rule
- First agent runs to completion, saves output to working directory
- Second agent starts, reads output files from first agent
- Each agent focuses on its domain — no scope creep across boundaries
Output convention
- Agents write deliverables to the working directory (markdown, JSON, PPTX, etc.)
- File names follow skill conventions (e.g.,
ecosystem-map.md, gap-analysis.md, top-20-profiles.md)
- Next agent reads these files as input — no need for explicit "handoff" mechanism
- If an agent produces structured data (JSON, tables), downstream agents should parse and reference it directly
Brand as shared state
- Brand is NOT an agent-to-agent handoff — it's shared context available to ALL content agents
brand/brand.json + brand/tone-of-voice.md are always checked before content creation
- Brand architect creates these files once; all content agents consume them automatically
CROSS-DOMAIN WORKFLOWS
Six common multi-agent workflows. Each specifies trigger, order, handoff, and example prompt.
1. Research → LinkedIn Post
- Trigger: "research" + "post" / "LinkedIn" / "write about findings"
- Order: market-researcher → content-creator (linkedin)
- Handoff: Research outputs
ecosystem-map.md, gap-analysis.md, top-20-profiles.md → LinkedIn skill reads findings as source material instead of doing own WebSearch
- Example: "Research the AI coding assistant market then write a LinkedIn post about the top insights"
2. Research → Pitch Deck / Carousel
- Trigger: "research" + "deck" / "carousel" / "presentation" / "slides"
- Order: market-researcher → content-creator (carousel/slides)
- Handoff: Research outputs competitor data, feature matrix, pricing benchmarks → carousel builds positioning deck using real data
- Example: "Analyze our competitors then create a pitch deck showing our positioning"
3. Brand → Any Content
- Trigger: "brand" + any content keyword (post, carousel, slides, SOP)
- Order: brand-architect → content-creator
- Handoff: Brand generates
brand/brand.json + brand/tone-of-voice.md → all content skills auto-detect and apply brand colors, fonts, voice
- Example: "Create our brand identity then make a LinkedIn carousel introducing the company"
4. Research → CEO Strategy
- Trigger: "research" + "strategy" / "positioning" / "where we stand"
- Order: market-researcher → ceo-strategist
- Handoff: Research outputs ecosystem map, pricing benchmarks, market gaps → CEO advisor uses for strategic positioning and decision-making
- Example: "Map the competitive landscape for project management tools then help me decide our strategic positioning"
5. Research → GTM Plan
- Trigger: "research" + "GTM" / "go-to-market" / "launch strategy"
- Order: market-researcher → sales-hunter + growth-marketer
- Handoff: Research outputs market map, ICP signals, competitor weaknesses → sales builds outbound strategy, marketing builds inbound strategy
- Example: "Research the developer tools market then build our go-to-market plan"
6. Full Content Pipeline
- Trigger: "brand" + "research" + content keywords (or explicit "full pipeline")
- Order: brand-architect → market-researcher → content-creator (parallel: linkedin + carousel + slides)
- Handoff: Brand first (creates visual/voice system) → research second (creates data/insights) → content last (uses both brand + research as inputs)
- Example: "We're launching next month — create our brand, research the market, then generate launch content across all channels"
7. Visual Media → Content
- Trigger: "find images" + content keyword, OR image layouts in carousel plan with no images provided
- Order: visual-media → content-creator (carousel/linkedin)
- Handoff: Visual-media saves images to
media/images/[topic-slug]/ → carousel uses paths in image layouts, linkedin recommends for post
- Example: "Find relevant images about AI coaching and create a carousel with them"
AVAILABLE COMMANDS
Startup Ops (existing)
/imperium:validate-idea — Startup idea validation
/imperium:pitch-deck — Pitch deck creation
/imperium:fundraise-prep — Fundraising preparation
/imperium:cold-email — Cold email campaigns
/imperium:competitor-matrix — Competitive matrix
/imperium:pricing-strategy — Pricing strategy
/imperium:gtm-plan — Go-to-market plan
/imperium:metrics-dashboard — SaaS metrics dashboard
/imperium:founder-kb — Knowledge base search
Research & Intelligence (new)
/imperium:deep-research — Full 9-phase competitive intelligence
/imperium:discover-apis — Hidden API discovery for any website
/imperium:crawl-check — Check imperium-crawl installation & capabilities
Content Creation (new)
/imperium:create-brand — Brand identity wizard (colors, fonts, voice)
/imperium:linkedin-post — LinkedIn viral post generator
/imperium:carousel — PPTX carousel/deck creation
/imperium:create-video — Video content (bridge to Remotion)
/imperium:create-slides — HTML presentation slides
/imperium:create-sop — SOP/runbook/playbook generator
/imperium:find-images — Image/video sourcing with visual AI review
Eval & Quality
/imperium:eval-loop — Automated structural checks and quality analysis
AVAILABLE AGENTS
Startup Ops (existing)
- ceo-strategist — Strategic decisions, fundraising, board prep
- cto-architect — Architecture, tech stack, scaling
- growth-marketer — Marketing campaigns, SEO, content
- sales-hunter — Outbound sales, pipeline, GTM
- product-analyst — PRD, roadmap, prioritization
Research & Content (new)
- market-researcher — Deep competitive intelligence, ecosystem mapping
- content-creator — LinkedIn posts, carousels, slides, SOPs, video
- brand-architect — Brand identity creation, voice definition
BRAND SYSTEM
Shared resource at brand/ — generated by /imperium:create-brand.
Files:
brand/brand.json — 10 colors, 3 fonts, asset paths
brand/config.json — Output settings (format, naming)
brand/brand-system.md — Design philosophy, visual rules
brand/tone-of-voice.md — Voice character, vocabulary, platform adaptations
brand/templates/ — 5 pre-built voice templates
Usage: Content skills auto-detect and apply brand. No brand = defaults + suggestion to create one.
EXTERNAL TOOL INTEGRATION
imperium-crawl (optional, npm)
Deep research uses imperium-crawl for bulk scraping, AI extraction, YouTube/Reddit mining.
- Check:
command -v imperium-crawl
- Install:
npm install -g imperium-crawl
- Falls back to WebSearch + WebFetch if not installed.
Remotion (optional, npm)
Video skill bridges to Remotion for MP4/animation creation.
- Check: look for
remotion.config.* or package.json with remotion dependency
- Install:
npx create-video@latest
- Falls back to HTML slides or carousel if not available.