القائمة
Estimate codebase cost-to-build, AI-assisted ROI, and fair-market valuation
يُحدَّد Prompt الذي يراجع المصدر أولًا بشكل افتراضي. يمكنك التبديل إلى أمر مباشر أو تنزيل نسخة محلية.
اقرأ SKILL.md وأي ملفات مرافقة يعرضها SkillsMP قبل أن تقرر التثبيت.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
يتجاوز الأمر المباشر Prompt المخصّص للمراجعة. افحص المصدر قبل تشغيله.
npx skills add https://github.com/adolfousier/opencrabs --skill cost-estimateيبقى الأمر في سطر واحد. مرّر أفقيًا لمراجعته كاملًا قبل النسخ.
تفضّل نسخة محلية؟ نزّل الملفات المتاحة حاليًا لدى SkillsMP.
استنادا إلى تصنيف SOC المهني
عرض SKILL.md
| name | cost-estimate |
| description | Estimate codebase cost-to-build, AI-assisted ROI, and fair-market valuation |
Scan this entire codebase and produce a professional cost estimate and valuation report. Analyze:
Codebase inventory: Count files, lines of code by language, modules, API integrations, external services, database schemas, UI components, and any complex subsystems.
Complexity assessment: Identify the hardest parts — real-time features, protocol implementations, security layers, multi-platform support, API integrations (especially government/enterprise APIs that require domain expertise), custom parsers, streaming, WebSocket/SSE, OAuth flows, etc.
Human team estimate: Calculate what a real development team would need to build this from scratch. Use current US market rates (2025-2026):
AI comparison: Estimate AI-assisted hours actually spent (based on git history, commit frequency, time span from first to latest commit). Calculate speed multiplier and value per hour.
Integration complexity: For each external integration (APIs, channels, protocols, third-party services), assess:
Test coverage and CI: Analyze what exists and what a production build would need:
#[test], #[tokio::test], #[rstest], proptest — not just #[test])Ongoing maintenance and operational cost: The hidden costs after "it works":
Fair market valuation: Before estimating valuation, ASK THE USER for context that affects the valuation model. Prompt them with:
"To produce an accurate valuation, I need some context:
- Business model — Is this OSS, SaaS, enterprise-licensed, consulting, or something else?
- Revenue — Any current MRR/ARR? If pre-revenue, is monetization planned?
- Traction — GitHub stars, clones, downloads, active users, community size?
- Team — Solo maintainer or team? Full-time or side project?
- Funding — Bootstrapped, funded, or seeking investment?
- Intent — Are you valuing for acquisition, fundraising, insurance, or just curiosity?"
Wait for the user's answers, then use the appropriate valuation methods:
Always include:
Include if applicable (based on user answers):
Revenue multiple — only if there's actual or planned revenue. Apply industry multiples (3-8x dev tools, 5-15x AI/infrastructure).
OSS traction valuation — if open source: use $/star benchmarks from historical acquisitions, community growth rate, clone/download metrics, projected trajectory.
Funding-stage valuation — if seeking investment: comparable seed/Series A rounds for similar dev tools.
Valuation summary table — show Low / Mid / High estimates across all applicable methods, then a blended fair market range.
Output a report with these sections:
Be thorough but honest. Base estimates on real market rates and realistic timelines. Don't inflate numbers — credibility matters more than impressive figures. The goal is to show the build cost, true cost of ownership, AND what the project is actually worth.