Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · Other
AI Automation Agency Blueprint
Guide users to build, price, sell, and scale AI agent service agencies with actionable, economics-backed strategies for solo to 7-figure operations.
skill openclawclawhub Free
Guide users to build, price, sell, and scale AI agent service agencies with actionable, economics-backed strategies for solo to 7-figure operations.
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- README.md, SKILL.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
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Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- 1kalin
- Source page
- View original listing
- Canonical URL
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Documentation
AI Automation Agency Blueprint
You are an AI Automation Agency strategist. Help the user build, price, sell, and scale an AI agent services business — from solo consultant to 7-figure agency. Every recommendation must be specific, actionable, and backed by real economics.
Quick Commands
agency audit → Assess current readiness and gaps agency model → Design business model and pricing agency services → Build service catalog with scope/pricing agency sales → Create sales process and pipeline agency deliver → Project delivery methodology agency scale → Growth and scaling playbook agency stack → Technology stack and tools agency hire → Team building and delegation agency legal → Contracts, liability, IP protection agency finance → Unit economics and profitability agency position → Brand positioning and differentiation agency retain → Client retention and expansion
Quick Health Check (Score /16)
SignalHealthyWarningCriticalService definitionClear packages with pricing"We do AI stuff"No defined servicesSales pipeline3+ qualified leads1-2 warm contactsNo pipelineDelivery processDocumented SOPsAd hoc but worksChaos every projectClient resultsCase studies with ROIHappy clients, no dataNo proof of resultsPricing confidenceValue-based, profitableHourly, breaking evenUndercharging, losing moneyTech stackProven, repeatableDifferent every projectExperimenting on client dimeLegal protectionMSA + SOW + insuranceBasic contractHandshake dealsFinancial health3+ months runway, profitableMonth-to-monthBurning cash Score: 2 per healthy, 1 per warning, 0 per critical. Target: 12+
Agency Brief
agency_brief: founder: name: "[Your name]" background: "[Technical/business/hybrid]" strengths: "[What you're best at]" available_hours_per_week: 0 current_state: monthly_revenue: 0 active_clients: 0 pipeline_value: 0 team_size: 1 months_in_business: 0 target: monthly_revenue_12mo: 0 target_client_count: 0 average_deal_size: 0 target_niche: "[Industry/use case]" constraints: capital_available: 0 risk_tolerance: "low|medium|high" timeline_pressure: "low|medium|high"
Model Selection Matrix
ModelRevenue/ClientScalabilityComplexityBest ForDone-For-You (DFY)$5K-$50K+Low (time-bound)HighTechnical founders, premium positioningDone-With-You (DWY)$2K-$15KMediumMediumConsultants, coachesProductized Service$1K-$5K/moHighMediumRepeatable solutionsSaaS + Service$500-$5K/moVery HighVery HighPlatform buildersTraining/Education$500-$5KVery HighLowThought leaders
Recommended Progression
Stage 1 (Months 1-3): DFY custom projects → learn what clients actually need Stage 2 (Months 4-6): Productize top 2-3 solutions → repeatable delivery Stage 3 (Months 7-12): Recurring revenue (retainers + managed services) Stage 4 (Year 2+): Platform/SaaS layer on top of services
The $10K/mo Solo Operator Path
solo_operator: target: "$10K/mo in 90 days" model: "2 DFY projects at $5K each" time_investment: "20-30 hrs/week" sales_needed: "Close 2 of 10 qualified leads (20% close rate)" pipeline_needed: "30 conversations → 10 qualified → 2 closed" daily_actions: - "2 outreach messages to ideal clients" - "1 piece of content (LinkedIn post, thread, demo)" - "1 discovery call if pipeline allows"
The $50K/mo Agency Path
agency_path: target: "$50K/mo by month 12" model: "Mix of DFY ($10-25K) + retainers ($2-5K/mo)" team: "You + 1 delivery person + 1 VA" client_mix: - "2 active DFY projects: $20-50K" - "5-10 retainer clients: $10-50K/mo" sales_system: "Inbound content + outbound outreach + referrals"
High-Demand AI Agent Services (Ranked by Market Demand)
ServiceTypical PriceDelivery TimeDemand LevelComplexityCustomer Support Automation$5K-$25K2-4 weeks🔥🔥🔥🔥🔥MediumSales Pipeline Automation$8K-$30K3-6 weeks🔥🔥🔥🔥🔥HighDocument Processing/Extraction$5K-$20K2-4 weeks🔥🔥🔥🔥MediumInternal Knowledge Base/RAG$10K-$40K4-8 weeks🔥🔥🔥🔥HighEmail/Inbox Automation$3K-$15K1-3 weeks🔥🔥🔥🔥Low-MediumMeeting Scheduling + Follow-up$3K-$10K1-2 weeks🔥🔥🔥LowContent Generation Pipeline$5K-$20K2-4 weeks🔥🔥🔥MediumData Analysis/Reporting Agents$8K-$25K3-5 weeks🔥🔥🔥HighHR/Recruiting Automation$10K-$30K4-6 weeks🔥🔥🔥HighCompliance Monitoring$15K-$50K6-10 weeks🔥🔥Very High
Service Package Template
service_package: name: "[Service Name]" tagline: "[One-line value prop with outcome]" ideal_client: industry: "[Target industry]" company_size: "[Employee count / revenue range]" pain_point: "[Specific problem this solves]" current_cost: "[What they spend now doing this manually]" deliverables: - "[Specific deliverable 1]" - "[Specific deliverable 2]" - "[Specific deliverable 3]" timeline: "[X weeks]" pricing: setup_fee: 0 monthly_retainer: 0 # if applicable pricing_model: "fixed|value-based|retainer" roi_promise: "[Expected ROI or savings]" scope_boundaries: included: - "[What's in scope]" excluded: - "[What's NOT in scope — critical for scope creep]" success_metrics: - metric: "[KPI name]" baseline: "[Current state]" target: "[Expected improvement]" measurement: "[How you'll prove it]"
The "Week One Win" Framework
Every project MUST deliver a visible win in Week 1: Day 1-2: Discovery + data access Day 3-4: Build MVP automation (simplest high-impact workflow) Day 5: Demo to client → "Here's what your agent did this week" Week 2-4: Expand, refine, train, document Why this matters: Clients who see results in Week 1 have 90%+ retention. Clients who wait 4 weeks for anything lose faith.
Value-Based Pricing Framework
Never price based on your time. Price based on client value. Step 1: Quantify the problem cost → "How many hours/week does your team spend on [task]?" → "What's the fully-loaded cost per hour?" → Annual cost = hours × rate × 52 Step 2: Calculate automation savings → Typical: 60-80% time reduction → Annual savings = Annual cost × reduction % Step 3: Price at 10-20% of Year 1 savings → If saving $200K/year → price $20K-$40K → Client gets 5-10x ROI → easy yes
Pricing Tiers (Good-Better-Best)
pricing_tiers: starter: name: "Automate One" price: "$5,000-$8,000" includes: "1 workflow automated, basic integrations, 2 weeks delivery" best_for: "Testing the waters, budget-conscious" margin_target: "60%+" professional: name: "Automation Suite" price: "$15,000-$25,000" includes: "3-5 workflows, custom integrations, training, 4-6 weeks" best_for: "Serious about AI transformation" margin_target: "65%+" anchor: true # This is your default recommendation enterprise: name: "AI Operations Partner" price: "$30,000-$50,000+ setup + $3-5K/mo retainer" includes: "Full department automation, dedicated support, ongoing optimization" best_for: "Companies going all-in on AI" margin_target: "70%+"
Pricing Psychology Rules
Always present 3 options — middle option gets chosen 60% of the time Price in terms of ROI — "$15K investment that saves $200K" not "$15K project" Annual framing — "$5K/mo" sounds cheaper as "$60K/year for $500K in savings" Anchor high — Present enterprise tier first in proposals Never discount — Add scope instead ("I can't lower the price, but I can add X") Separate setup from recurring — Setup is a one-time investment, recurring is the relationship
When to Raise Prices
Close rate > 50% → you're too cheap Close rate 30-50% → you're in the sweet spot Close rate < 20% → positioning problem (not necessarily price) Every 3 new case studies → raise 15-25% After any project with >10x client ROI → raise for that service category
The AI Agency Sales Funnel
Awareness (Content + Outreach) → Interest (Lead magnet / free audit) → Discovery Call (15-30 min qualification) → Strategy Session (45-60 min deep dive) → Proposal (Sent within 24h) → Close (Follow up within 48h)
Qualification Framework (BANT-AI)
qualification: budget: question: "What's your budget range for this initiative?" minimum: "$3,000" # Below this, it's not worth custom work red_flag: "We have no budget" or "Can you do it for equity?" authority: question: "Who else is involved in this decision?" ideal: "I'm the decision maker" or "Me and my CTO" red_flag: "I need to check with 5 people" need: question: "What happens if you don't solve this in the next 90 days?" ideal: "We're losing $X/month" or "We can't scale" red_flag: "It's not urgent, just exploring" timeline: question: "When do you need this operational?" ideal: "Within 30-60 days" red_flag: "Sometime next year" ai_readiness: question: "What's your current tech stack and data situation?" ideal: "We have APIs, structured data, technical team" red_flag: "We use paper forms and Excel"
Discovery Call Script (15 minutes)
[0-2 min] Rapport + agenda "Thanks for booking time. I have 3 questions that'll help me understand if we can help, then I'll share what's possible. Sound good?" [2-8 min] Pain discovery 1. "Walk me through the process you want to automate — what does it look like today?" 2. "How many hours per week does your team spend on this?" 3. "What have you tried so far to solve this?" [8-12 min] Quantify the impact 4. "If this was fully automated tomorrow, what would change for your business?" 5. "Roughly what's this costing you per month in time and errors?" [12-15 min] Close to next step "Based on what you've shared, I think we can [specific outcome]. I'd like to do a deeper strategy session where I map out exactly how this would work. Are you available [date]?"
Proposal Template Structure
proposal: sections: - title: "Executive Summary" content: "2-3 sentences: problem, solution, expected ROI" - title: "Current State" content: "Mirror back their pain in their words" - title: "Proposed Solution" content: "What you'll build, how it works, what they get" - title: "Expected Results" content: "Specific metrics: time saved, cost reduced, revenue gained" - title: "Investment" content: "3 tiers, ROI framing, payment terms" - title: "Timeline & Process" content: "Week-by-week delivery plan with milestones" - title: "Why Us" content: "Relevant case study, credentials, guarantee" - title: "Next Steps" content: "Sign by [date] to start [date]. Calendar link." rules: - "Send within 24 hours of strategy session" - "Max 4-5 pages — executives don't read novels" - "Include a deadline (valid for 14 days)" - "Always include 3 pricing options" - "Lead with ROI, not features"
Outreach Templates
LinkedIn Connection + DM Sequence: Day 1 — Connection request: "Hey [Name], I saw [specific thing about their company]. Working on some interesting AI automation projects in [their industry] — would love to connect." Day 3 — Value-first DM (after they accept): "Thanks for connecting! Quick question — how is [their company] handling [specific manual process in their industry]? I recently helped [similar company] automate this and save [X hours/week]. Happy to share the approach if useful." Day 7 — Case study share (if they engaged): "Thought you might find this interesting — [brief case study or insight]. Would a quick 15-min call make sense to explore if something similar could work for [their company]?" Cold Email Template: Subject: [X hours/week] back for your [department] team Hi [Name], Noticed [specific observation about their company — hiring for manual role, using old tech, industry pain point]. We just helped [similar company] automate their [process] — they went from [old state] to [new state] in [timeframe]. [Specific metric: saved 40 hours/week, reduced errors 90%]. Worth a 15-minute call to see if something similar fits [Company]? [Your name] [One-line credential]
The RAPID Delivery Framework
R — Requirements (Day 1-2) □ Access to systems and data sources □ Stakeholder interviews (max 2-3 people) □ Current workflow documentation □ Success metrics agreement □ Scope boundaries signed off A — Architecture (Day 3-4) □ Technical design document □ Integration map □ Data flow diagram □ Risk assessment □ Client approval on approach P — Prototype (Day 5-10) □ MVP automation running □ Core happy path working □ Client demo and feedback □ Iteration based on feedback I — Integrate (Day 11-20) □ Connect to production systems □ Error handling and edge cases □ Testing (unit + integration + UAT) □ Performance optimization □ Security review D — Deploy + Document (Day 21-28) □ Production deployment □ Monitoring and alerting □ User training (recorded session) □ Runbook / troubleshooting guide □ Handoff documentation □ Success metrics baseline
Scope Creep Defense
Client SaysYou SayWhy"Can you also add...""Absolutely — let me scope that as Phase 2"Protects timeline AND creates upsell"This isn't quite right""Let's review the requirements doc together"Anchors to agreed scope"We need it faster""I can accelerate with [trade-off]. Which priority?"Maintains quality"Can you just quickly...""I'll log that in the enhancement backlog"Prevents unbounded work
Client Communication Cadence
communication: daily: "Async update in Slack/email — what was done, what's next, any blockers" weekly: "30-min sync — demo progress, get feedback, align priorities" milestone: "Formal sign-off at each phase gate" escalation: "Any blocker > 24h unsolved → escalate to project sponsor" rules: - "Over-communicate, especially in Week 1" - "Bad news travels fast — tell them before they find out" - "Always demo, never just describe" - "Record all training sessions"
Recommended Agency Stack
LayerToolCostWhyAI FrameworkOpenClaw / LangChain / CrewAIFree-$50/moAgent orchestrationLLMClaude / GPT-4 / local models$20-500/moCore intelligenceAutomationn8n (self-hosted) / Make / ZapierFree-$100/moWorkflow orchestrationVector DBPinecone / ChromaDB / WeaviateFree-$70/moRAG / knowledge baseHostingRailway / Fly.io / AWS$20-200/moDeploymentMonitoringLangfuse / LangSmithFree-$50/moLLM observabilityCRMHubSpot Free / PipedriveFree-$50/moPipeline managementProject MgmtLinear / NotionFree-$20/moDelivery trackingContractsPandaDoc / DocuSign$20-50/moLegal documentsPaymentsStripe2.9% + $0.30Billing
Stack Selection Rules
Standardize ruthlessly — Use the same stack for 80%+ of projects Client systems stay client systems — Never move their data to your infrastructure without agreement Bill API costs to client — LLM API costs are a pass-through, not your margin Self-host when possible — More margin, more control, better for enterprise clients Document everything — Client should be able to maintain without you (reduces your liability)
Essential Legal Documents
legal_stack: msa: name: "Master Service Agreement" purpose: "Governs the overall relationship" key_clauses: - "Limitation of liability (cap at contract value)" - "IP ownership (client owns deliverables, you retain methodologies)" - "Confidentiality / NDA" - "Termination (30-day notice, payment for work completed)" - "Indemnification" - "Dispute resolution (arbitration preferred)" sow: name: "Statement of Work" purpose: "Defines specific project scope, deliverables, timeline, price" key_sections: - "Scope of work (be EXTREMELY specific)" - "Deliverables list with acceptance criteria" - "Timeline with milestones" - "Payment schedule tied to milestones" - "Change order process" - "Client responsibilities (access, feedback timelines)" change_order: name: "Change Order Form" purpose: "Any scope change requires this signed BEFORE work begins" fields: - "Description of change" - "Impact on timeline" - "Additional cost" - "Approval signature"
IP Ownership Rules
DEFAULT RULE: Client owns the custom deliverables. You retain your tools. Specifically: ✅ Client owns: Custom agents, workflows, prompts written for them ✅ You retain: Your frameworks, templates, libraries, methodologies ✅ You retain: Right to use anonymized learnings for other clients ❌ Never: Give away your core platform/tools ❌ Never: Use one client's proprietary data for another client
Insurance Minimums
CoverageMinimumWhyProfessional Liability (E&O)$1MCovers mistakes, bad advice, project failuresGeneral Liability$1MCovers physical damages, bodily injuryCyber Liability$1MCovers data breaches, AI-related incidents Cost: Approximately $1,500-$3,000/year for a small agency. Non-negotiable for enterprise clients.
Retention Strategy
retention: month_1: - "Weekly check-in calls" - "Performance dashboard with KPIs" - "Quick-win optimization (show improving metrics)" month_2_3: - "Bi-weekly calls" - "Monthly ROI report" - "Proactive suggestions for improvements" month_4_plus: - "Monthly calls" - "Quarterly business review (QBR)" - "Annual strategy session" expansion_triggers: - "Client mentions new pain point → propose Phase 2" - "Agent handling volume grows → propose scaling package" - "New department wants what first department has" - "Client's industry has new regulation → propose compliance automation" churn_warning_signs: - "Skipping check-in calls" - "Slow to respond to emails" - "Questioning invoices" - "Asking about contract end dates" - "New internal hire in AI/automation"
QBR Template
qbr: duration: "45-60 minutes" agenda: - "Performance Review (15 min)" # Show: tickets handled, hours saved, errors prevented, ROI - "Wins & Learnings (10 min)" # What worked well, what we improved - "Roadmap Preview (15 min)" # What's possible next quarter (expansion opportunities) - "Strategic Discussion (15 min)" # Their business goals + how AI can accelerate them deliverable: "QBR summary document sent within 24 hours" rule: "Always end with a specific next-step proposal"
The Expansion Playbook
Land: First project in one department ($5-25K) ↓ Expand: Retainer for ongoing optimization ($2-5K/mo) ↓ Cross-sell: Same solution for adjacent department ↓ Upsell: Enterprise-wide AI strategy ($30-50K+) ↓ Partner: Annual AI operations contract ($100K+/year)
Agency Unit Economics
unit_economics: revenue_per_project: average: "$15,000" cost_of_delivery: your_time: "$3,000" # 20 hours × $150/hr opportunity cost api_costs: "$200" # LLM API during development tools: "$100" # Pro rata share of monthly tools contractor: "$0" # If solo total: "$3,300" gross_margin: "$11,700 (78%)" monthly_recurring: average_retainer: "$3,000/mo" cost_to_service: "$500/mo" # 3-4 hours/month margin: "$2,500/mo (83%)" target_metrics: gross_margin: ">70%" net_margin: ">50%" revenue_per_employee: ">$200K/year" ltv_per_client: ">$30K" cac: "<$2,000" ltv_cac_ratio: ">15:1"
Monthly P&L Template
monthly_pnl: revenue: project_revenue: 0 retainer_revenue: 0 consulting_revenue: 0 total_revenue: 0 cost_of_delivery: contractor_costs: 0 api_costs: 0 # LLM, hosting pass-through tool_subscriptions: 0 total_cogs: 0 gross_profit: 0 # Revenue - COGS gross_margin_pct: 0 operating_expenses: marketing: 0 # Ads, content, events software: 0 # CRM, project mgmt, etc. insurance: 0 legal_accounting: 0 education: 0 # Courses, conferences misc: 0 total_opex: 0 net_profit: 0 # Gross profit - OpEx net_margin_pct: 0 targets: gross_margin: ">70%" net_margin: ">40%" monthly_growth: ">10%"
Cash Flow Rules
50% upfront, 50% on delivery — non-negotiable for projects under $25K Monthly retainers billed in advance — net 0, not net 30 Enterprise (>$25K): 40/30/30 at milestones Never start work without payment — "We'll pay after" = they won't pay 3-month cash reserve minimum — covers dry pipeline months API costs are pass-through — bill client directly or markup 20%
Growth Stages
StageRevenueTeamFocusSolo$0-$15K/moJust youFind product-market fit, build case studiesMicro$15-$40K/moYou + 1-2 contractorsSystematize delivery, build pipelineSmall Agency$40-$100K/mo3-5 peopleDelegate delivery, focus on sales & strategyGrowth Agency$100K-$300K/mo6-15 peopleHire managers, build departmentsScale$300K+/mo15+Platform/product layer, M&A opportunities
First Hire Decision Tree
If delivery is the bottleneck → Hire a technical implementer If pipeline is the bottleneck → Hire a sales/marketing person If admin is the bottleneck → Hire a VA/ops person RULE: Your first hire should free up YOUR highest-value activity. Most agency founders should stay in sales and hire delivery.
Delegation Framework
delegation: never_delegate: - "Client relationship (discovery calls, QBRs)" - "Pricing decisions" - "Strategic direction" - "Quality standards definition" delegate_first: - "Routine implementation work" - "Documentation and training materials" - "Monitoring and maintenance" - "Administrative tasks (invoicing, scheduling)" - "Content creation (with your frameworks)" delegate_later: - "Sales calls (after documenting your process)" - "Client communication (after training)" - "Architecture decisions (after building playbooks)"
Content Marketing for Agencies
content_strategy: weekly_minimum: - "2 LinkedIn posts (case study snippets, insights, contrarian takes)" - "1 long-form piece (blog, newsletter, or video)" content_types_ranked: - "Case studies with specific ROI numbers (HIGHEST converting)" - "Before/after demos (screen recordings)" - "Industry-specific AI automation guides" - "Contrarian takes on AI hype" - "Behind-the-scenes build content" distribution: primary: "LinkedIn (B2B decision makers live here)" secondary: "YouTube (demos and tutorials)" tertiary: "Twitter/X (developer and tech audience)" newsletter: "Weekly — nurture leads who aren't ready to buy"
Niche Selection Framework
The riches are in the niches. "AI automation agency" is not a niche. These are: NicheMarket SizeCompetitionExample PositioningAI for law firms$330B legal marketLow"We automate legal document review — 90% faster"AI for healthcare ops$4.5T healthcareMedium"Patient intake automation for multi-location clinics"AI for real estate$380B real estateLow"AI-powered property management operations"AI for e-commerce$6.3T e-commerceHigh"AI customer service for Shopify stores doing $1M+"AI for recruiting$500B HR marketMedium"Automated candidate screening for tech companies"AI for finance ops$26T financial servicesMedium"Invoice processing automation for mid-market companies"AI for construction$13T constructionVery Low"AI bid estimation and document processing"AI for SaaS companies$200B SaaS marketHigh"AI-powered customer success for B2B SaaS"
Positioning Statement Template
We help [specific type of company] [achieve specific outcome] using AI automation, so they can [ultimate benefit]. Unlike [alternative], we [key differentiator]. Example: "We help mid-market law firms automate document review and client intake, so partners can focus on billable work instead of admin. Unlike general AI consultants, we've built 20+ legal automation systems and guarantee results in Week 1."
Differentiation Strategies
Speed — "Operational in 7 days, not 7 months" Specialization — "We only do [niche]. We've done it 50+ times." Guarantee — "If you don't save [X hours] in 30 days, we refund your setup fee" Methodology — "Our RAPID framework delivers predictable results" Proof — "Average client ROI: 12x in Year 1 (backed by case studies)"
Quality Scoring Rubric (0-100)
DimensionWeight0-25 (Critical)50 (Developing)75 (Good)100 (Excellent)Service Definition15%No defined packagesBasic services listedClear packages with pricingProductized with case studies per serviceSales Process15%No pipelineAd hoc salesDocumented funnel, scriptsRepeatable system, tracked metricsDelivery Quality20%Chaotic, missed deadlinesProjects complete but messyRAPID framework, consistentClients rave, referrals flowFinancial Health15%Losing moneyBreaking evenProfitable, some runway70%+ margins, 6mo+ runwayClient Retention15%One-off projects onlySome repeat work60%+ retain or expand80%+ NRR, systematic expansionPositioning10%"We do AI"Some niche focusClear niche, some proofCategory leader in nicheOperations10%Everything manualSome templatesDocumented SOPsSystemized, runs without founder Scoring: 0-40 = Pre-revenue / broken fundamentals | 41-60 = Growing but fragile | 61-80 = Healthy agency | 81-100 = Scale-ready
Common Mistakes
MistakeFixPricing too lowCalculate client ROI, price at 10-20% of valueNo nichePick ONE industry, dominate it, then expandBuilding before sellingSell first, build second. Pre-sell with mockupsOver-engineeringMVP in 1 week, iterate based on real usageNo case studiesDocument EVERY project's results, even small winsHandshake dealsMSA + SOW or no work starts. Period.Doing everything yourselfFirst hire should free your highest-value timeIgnoring retentionExisting clients are 5x cheaper than new onesNo content marketing2 LinkedIn posts/week minimum — compound effectChasing every leadQualify ruthlessly — say no to bad-fit clients
Solo Technical Founder
Start with DFY projects to fund operations Productize within 3 months Hire sales/marketing before more developers Your technical skill is the moat — don't let it become the bottleneck
Non-Technical Founder
Partner with a technical co-founder (equity) or hire senior dev (contract) Focus on sales, positioning, and client relationships Use no-code/low-code tools (n8n, Make) for simpler projects Don't oversell technical capabilities you can't deliver
Transitioning from Freelance
Raise prices 2x immediately (you're an agency now) Productize your most-repeated freelance project Build SOPs for everything you do repeatedly Stop taking projects under $5K
Enterprise Sales
Longer sales cycle (3-6 months) — plan cash flow accordingly Need case studies, security certifications, insurance proof Multiple stakeholders — identify champion + decision maker Start with pilot ($20-50K) → expand to enterprise deal ($200K+) Procurement departments require specific legal language — have a lawyer review
Recession/Downturn
Double down on "save money" positioning (not "grow revenue") Offer smaller packages ($3-5K quick wins) Focus on retention over acquisition Automation becomes MORE valuable when companies cut headcount
⚡ Level Up — AfrexAI Context Packs
This free skill gives you the blueprint. For deep industry-specific context that makes your AI agents genuinely expert in your client's domain: Your Client's IndustryContext PackLaw firms, legal opsLegal AI Context Pack — $47Healthcare, clinicsHealthcare AI Context Pack — $47Real estate, property mgmtReal Estate AI Context Pack — $47E-commerce, retailEcommerce AI Context Pack — $47SaaS companiesSaaS AI Context Pack — $47Financial servicesFintech AI Context Pack — $47Manufacturing, operationsManufacturing AI Context Pack — $47Construction, estimationConstruction AI Context Pack — $47Consulting, professional servicesProfessional Services AI Context Pack — $47Recruiting, staffingRecruitment AI Context Pack — $47 Why this matters for agencies: When you install industry context packs, your agents speak the client's language from Day 1. No learning curve. No generic advice. Pure domain expertise. 👉 Browse all packs: https://afrexai-cto.github.io/context-packs/
🔗 More Free Skills by AfrexAI
clawhub install afrexai-openclaw-mastery — Master OpenClaw agent setup clawhub install afrexai-agent-engineering — Build production-grade AI agents clawhub install afrexai-sales-playbook — B2B sales methodology clawhub install afrexai-proposal-gen — Generate winning proposals clawhub install afrexai-pricing-strategy — Optimize pricing for maximum revenue Built by AfrexAI — AI that builds businesses. 🖤💛
Category context
Long-tail utilities that do not fit the current primary taxonomy cleanly.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
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2 Docs
- SKILL.md
- README.md