GP Performance Evaluator
Analyze General Partner performance against vintage peer benchmarks. Computes fee drag (gross-to-net spread), DPI/TVPI/IRR vs vintage peers, deal-level return dispersion, key person risk, style drift detection, and produces a GP scorecard with performance, fees, risk, and re-up recommendation. Branches by fund strategy (core, value-add, opportunistic), fund vintage, and fund size. Triggers on 'GP performance', 'GP evaluation', 'GP track record', 'vintage benchmark', 'fee drag', 'gross to net spread', 'fund performance analysis', 'manager evaluation', 'GP scorecard', 'DPI TVPI comparison', 'fund quartile ranking', or when an LP needs to evaluate a GP's quantitative performance.
What this skill does
GP Performance Evaluator is an A.CRE Intelligence Hub skill that gives your AI agent the analyst-grade workflow a senior commercial real estate professional would run. Analyze General Partner performance against vintage peer benchmarks. Computes fee drag (gross-to-net spread), DPI/TVPI/IRR vs vintage peers, deal-level return dispersion, key person risk, style drift detection, and produces a GP scorecard with performance, fees, risk, and re-up recommendation. Branches by fund strategy (core, value-add, opportunistic), fund vintage, and fund size. Triggers on 'GP performance', 'GP evaluation', 'GP track record', 'vintage benchmark', 'fee drag', 'gross to net spread', 'fund performance analysis', 'manager evaluation', 'GP scorecard', 'DPI TVPI comparison', 'fund quartile ranking', or when an LP needs to evaluate a GP's quantitative performance. Analyze General Partner performance against vintage peer benchmarks. Computes fee drag gross-to-net spread , DPI/TVPI/IRR vs vintage peers, deal-level return dispersion, key person risk, style drift detection, and produces a GP scorecard with performance, fees, risk, and re-up recommendation.
How you'll use it
Say something like this to your AI agent in the Hub, Claude, or ChatGPT to activate this skill.
What you give it / What you get back
You give it
See the SKILL.md preview below.
You get back
- 3/5 (second quartile
- average
Skill activation rules
Detailed routing logic, prompts the skill responds to, and operational guardrails as documented by the author.
Analyze General Partner performance against vintage peer benchmarks. Computes fee drag (gross-to-net spread), DPI/TVPI/IRR vs vintage peers, deal-level return dispersion, key person risk, style drift detection, and produces a GP scorecard with performance, fees, risk, and re-up recommendation. Branches by fund strategy (core, value-add, opportunistic), fund vintage, and fund size. Triggers on 'GP performance', 'GP evaluation', 'GP track record', 'vintage benchmark', 'fee drag', 'gross to net spread', 'fund performance analysis', 'manager evaluation', 'GP scorecard', 'DPI TVPI comparison', 'fund quartile ranking', or when an LP needs to evaluate a GP's quantitative performance.
What's inside
GP Performance Evaluator
You are a senior quantitative analyst at an institutional LP with deep expertise in CRE fund performance measurement, benchmarking, and attribution. You evaluate GP-reported data with forensic precision -- verifying calculations, decomposing returns,…
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GP Performance Evaluator
You are a senior quantitative analyst at an institutional LP with deep expertise in CRE fund performance measurement, benchmarking, and attribution. You evaluate GP-reported data with forensic precision -- verifying calculations, decomposing returns, and placing performance in vintage peer context. Your analysis separates genuine manager skill from market beta, leverage amplification, and luck.
Your output directly informs re-up decisions worth tens or hundreds of millions of dollars. A GP that appears top-quartile on gross returns may be median on a net basis after fee drag. A GP with strong TVPI may have poor DPI because the portfolio is unrealized and NAV marks are questionable. You see through these nuances.
When to Activate
Full instructions and any reference files ship in the .skill bundle.
gp-performance-evaluator/
├── SKILL.md # Required: instructions + metadata
└── references/ # Optional: documentation
├── fee-analysis-methodology.md # 10.1 KB
├── gp-scoring-rubric.md # 11.5 KB
└── vintage-benchmarks.yaml # 10.0 KB
How to run it
Not in the Hub? Download the .skill bundle above and follow the A.CRE skills install guide → to load it into Claude Desktop, ChatGPT, Cursor, or any other agent that supports skills.
Already in the Hub. If you're an AI.Edge Pro or A.CRE Accelerator member, this skill is bundled into the A.CRE Intelligence Hub direct connector (MCP server) — just ask your agent.