Awesome-Claude-Skills I built 135 Claude Skills with real formulas. Here's what "production-grade" actually means.

Most "Claude prompt" collections are ineffective because they rely on shallow roleplay or generic instructions rather than actual expertise. To address this, they built AgentOS 2.0, a collection of 135 "production-grade" Claude Skills that include real, runnable Python code (such as Black-Scholes and Black-Litterman formulas), named sub-agents with distinct responsibilities, and explicit constraints to prevent hallucinations. The article contrasts these skills with common prompt traps, emphasizing that true production readiness requires domain-specific formulas and frameworks, not just persona-based prompts.

I've been frustrated for a long time. Every "awesome Claude prompts" repo I found looked like this: "Act as a senior software engineer. Be helpful, thorough, and professional. Consider edge cases." That's not a skill. That's a costume. Real expertise has frameworks . Named responsibilities. Actual formulas. Code that runs. Constraints that prevent the model from giving you the easy wrong answer. So I spent 6 months building what I actually wanted. AgentOS 2.0 — 135 production-grade Claude Skills. This article explains exactly what's inside and why it's different from every other prompt collection on GitHub. The Problem With Every Other Prompt Repo Most prompt repositories fall into one of three traps: Trap 1: The costume prompt "You are an expert financial analyst. Help the user with their finance questions." Zero frameworks. Zero formulas. Zero depth. Trap 2: The instruction dump "When answering, always: - Be professional - Consider multiple angles - Cite sources - Format your response clearly" This is just asking Claude to be Claude. It changes nothing. Trap 3: The persona prompt "You are Alex, a no-nonsense McKinsey consultant with 20 years of experience..." Roleplay, not expertise. The model doesn't suddenly know DCF models because you named it Alex. What actually works: Named sub-agents with distinct responsibilities, actual domain formulas in code, and explicit forbidden behaviors that prevent hallucination in critical areas. Here's what that looks like in practice. What "Production-Grade" Actually Looks Like FinanceOracle — The Apex Skill This is the most complete skill in the repo. Here's a fraction of what's inside: 12 Sub-Agents: - OptionsDesk — derivatives pricing and structuring - MacroStrategist — macro regime analysis - HedgeFundArchitect — strategy design - FamilyOfficeCIO — multi-generational allocation - TaxOptimizer — harvest and structure optimization - DerivativesStructurer — exotic product design + 6 more Actual runnable Python: python def black scholes S, K, T, r, sigma, option type='call' : d1 = np.log S/K + r + 0.5 sigma 2 T / sigma np.sqrt T d2 = d1 - sigma np.sqrt T if option type == 'call': price = S norm.cdf d1 - K np.exp -r T norm.cdf d2 delta = norm.cdf d1 else: price = K np.exp -r T norm.cdf -d2 - S norm.cdf -d1 delta = -norm.cdf -d1 gamma = norm.pdf d1 / S sigma np.sqrt T vega = S norm.pdf d1 np.sqrt T / 100 theta = - S norm.pdf d1 sigma / 2 np.sqrt T - r K np.exp -r T norm.cdf d2 / 365 return {"price": price, "delta": delta, "gamma": gamma, "vega": vega, "theta": theta} Black-Litterman portfolio construction: python def black litterman Sigma, market weights, views P, views Q, views omega, tau=0.05, delta=2.5 : pi = delta Sigma @ market weights M inv = np.linalg.inv np.linalg.inv tau Sigma + views P.T @ np.linalg.inv views omega @ views P mu bl = M inv @ np.linalg.inv tau Sigma @ pi + views P.T @ np.linalg.inv views omega @ views Q return {"expected returns": mu bl} This isn't pseudocode. This runs. OKREngine — Catches Failures Before They Kill Your Quarter I've watched two startups waste entire quarters on broken OKRs. This skill exists because of that. The objective quality scorer: php def score okr objective: str, key results: list dict - dict: obj score = 0 obj score += 3 if len objective < 100 else 0 obj score += 3 if not objective.lower .startswith "improve" else 0 obj score += 4 if any w in objective.lower for w in "best", "lead", " 1", "transform", "redefine" else 0 kr scores = for kr in key results: kr score = 0 kr score += 3 if kr.get "metric" else 0 kr score += 3 if kr.get "baseline" is not None else 0 kr score += 4 if kr.get "target" is not None else 0 kr scores.append { "kr": kr "text" :60 , "score": kr score, "grade": "Good" if kr score = 8 else "Needs work" } return { "objective score": f"{obj score}/10", "key results": kr scores, "recommendation": "Strong OKR" if obj score = 8 else "Needs revision" } The skill also catches the 12 most common OKR failure modes — including sandbagging, health metrics disguised as OKRs, and the single most destructive mistake: tying OKR scores to bonuses. VentureIntelligence — Term Sheet Red Flag Detector php def score term sheet terms: dict - dict: red flags = if terms.get "liq pref multiple", 1 1: red flags.append f"Liquidation preference {terms 'liq pref multiple' }x — above 1x is punishing" if terms.get "participating preferred", False : red flags.append "Participating preferred — VCs get paid twice in exits below threshold" if terms.get "anti dilution" == "full ratchet": red flags.append "Full ratchet anti-dilution — catastrophic in a down round" if terms.get "board seats investor", 0 terms.get "board seats founder", 0 : red flags.append "Investor has majority board control — you can be fired from your company" score = 10 - len red flags 3 return { "score": max 0, score , "grade": "Sign it" if score = 8 else "Negotiate" if score = 5 else "Get a lawyer NOW", "red flags": red flags } 12 sub-agents including TermSheetDecoder , ValuationNegotiator , ChampionDeveloper , and BoardRelationshipManager . CrisisIntelligence — War Room OS Every company will face a crisis. Almost none prepare. php def classify crisis crisis: dict - dict: severity score = 0 if crisis "customer impact pct" = 0.5: severity score += 30 if crisis "revenue at risk" = 1 000 000: severity score += 20 coverage = {"none": 0, "local": 5, "national": 15, "viral": 30} severity score += coverage.get crisis "media coverage" , 0 if crisis "regulatory involvement" : severity score += 15 if crisis "legal liability" : severity score += 15 if severity score = 70: level = "CRITICAL P0 " action = "CEO leads. War room activated NOW." elif severity score = 40: level = "HIGH P1 " action = "VP-level lead. External comms needed." else: level = "MEDIUM P2 " action = "Director-level. Monitor externally." return { "level": level, "immediate action": action, "time to first response": "1 hour" if severity score = 70 else "4 hours" } The 5Rs framework Recognize → Respond → Responsible → Remediate → Restore is built into every communication template. How It Works 60-Second Setup Claude.ai Projects: 1. Open Claude.ai → Projects → New Project 2. Paste SKILL.md into "Project Instructions" 3. Start chatting Claude Code: cat finance-oracle/SKILL.md .claude/CLAUDE.md Claude API: python import anthropic with open "startup-cto/SKILL.md", "r" as f: skill = f.read client = anthropic.Anthropic response = client.messages.create model="claude-sonnet-4-6", max tokens=4096, system=skill, messages= {"role": "user", "content": "Audit our tech stack decision"} That's it. Claude is now that specialist. The Full 135-Skill Index 🚀 Startup & Team Management 11 startup-cto team-performance-os startup-hiring-machine culture-architect remote-team-commander okr-engine startup-finance-controller venture-intelligence startup-legal-shield talent-management-os talent-brand-builder 🏆 Apex Legendary 4 finance-oracle claude-mythos ceo-war-room founder-to-ceo 🤖 AI & Engineering 14 rag-architect mlops-engineer system-architect senior-dev ai-red-teamer voice-agent-builder knowledge-graph-builder incident-commander mcp-builder agentic-workflow-builder api-integrator realtime-data-agent agent-smith prompt-engineer 📊 Data & Analytics 10 data-scientist-pro sql-analyzer data-pipeline-pro business-intelligence-pro timeseries-oracle quant-trader synthetic-data-generator arxiv-researcher abtest-scientist data-governance-agent 💹 Finance 9 finance-oracle financial-model-builder cfo-intelligence portfolio-optimizer quant-researcher saas-metrics-analyst insurance-actuary ma-dealmaker risk-sentinel 🏢 Operations & Business 20 ceo-war-room founder-to-ceo go-to-market-commander enterprise-sales-os sales-enablement-os board-deck-builder crisis-intelligence partnership-intelligence pricing-strategist project-command marketing-os supply-chain-oracle + 8 more 👤 Product & Customer 11 product-roadmap-os sprint-master engineering-manager ai-product-manager user-research-os customer-interview-analyst product-analytics-os network-effects-analyst marketplace-strategist performance-marketing-os churn-analyst 🛠 Developer Tools 19 developer-experience-os api-design-architect data-warehouse-architect cloud-cost-optimizer design-system-architect technical-pm code-reviewer load-tester code-migrator webapp-tester + 9 more 🌐 Specialized Domains 12 healthcare-analytics web3-developer climate-tech-analyst biotech-analyst cybersecurity-analyst real-estate-intelligence legal-eagle patent-analyst esg-compass + 3 more What Makes This Different From Every Other Repo | Feature | Generic repos | AgentOS 2.0 | |---|---|---| | Sub-agents | ❌ | ✅ 10-12 per skill | | Actual formulas | ❌ | ✅ Black-Scholes, DCF, MEDDPICC | | Runnable code | ❌ | ✅ Python, TypeScript, Go, Shell | | Forbidden behaviors | ❌ | ✅ Every skill | | Benchmark data | ❌ | ✅ Industry standards built in | | Total skills | ~10-20 | 135+ | Try It Right Now The fastest way to understand the depth is to try one. I recommend starting with okr-engine or — they're the most complete and immediately useful regardless of what you're building. startup-cto Paste the SKILL.md into Claude Projects. Ask it to review your current OKRs or tech stack. You'll see the difference immediately. GitHub link in the comments. What skill would you build your work around? Drop it below — I read every comment and I'm actively building more. MIT License. Free forever. Star it if it's useful — helps others find it.