pricing-lp-interest-portfolios
Evaluates LP interest portfolios with fund-by-fund NAV assessment, J-curve positioning, and portfolio-level pricing methodology. Use when pricing secondary portfolios, evaluating LP interest bids, or analyzing fund vintages.
Best use case
pricing-lp-interest-portfolios is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Evaluates LP interest portfolios with fund-by-fund NAV assessment, J-curve positioning, and portfolio-level pricing methodology. Use when pricing secondary portfolios, evaluating LP interest bids, or analyzing fund vintages.
Teams using pricing-lp-interest-portfolios should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/pricing-lp-interest-portfolios/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How pricing-lp-interest-portfolios Compares
| Feature / Agent | pricing-lp-interest-portfolios | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Evaluates LP interest portfolios with fund-by-fund NAV assessment, J-curve positioning, and portfolio-level pricing methodology. Use when pricing secondary portfolios, evaluating LP interest bids, or analyzing fund vintages.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Pricing Lp Interest Portfolios Evaluates LP interest portfolios with fund-by-fund NAV assessment, J-curve positioning, and portfolio-level pricing methodology. ## When To Use - Pricing a portfolio of LP interests for a secondary sale or bid evaluation - Assessing an incoming secondary bid against internal fair value estimates - Performing vintage-year analysis across a multi-fund LP book - Supporting investment committee memos with fund-by-fund NAV discount/premium rationale - Evaluating GP-led continuation vehicle pricing relative to LP secondary alternatives ## Inputs To Gather - **Fund-level data**: Most recent GP-reported NAV, NAV date, fund vintage year, strategy (buyout, growth, venture, credit, real assets), fund size, and GP name - **Cash flow history**: Capital called to date, distributions to date, remaining unfunded commitment per fund - **J-curve indicators**: Fund age relative to typical investment period, % invested, DPI and RVPI multiples - **GP quarterly reports**: Underlying portfolio company revenue/EBITDA multiples, write-ups/write-downs, and exit pipeline commentary - **Market benchmarks**: Recent secondary transaction pricing by strategy and vintage (e.g., Greenhill, Jefferies, Evercore secondary market reports) [VERIFY: confirm availability of latest quarterly secondary pricing data] - **Buyer constraints**: Target IRR/MOIC, portfolio concentration limits, GP relationship considerations ## Workflow 1. **Organize the portfolio into fund-level line items.** For each fund, record: GP name, vintage, strategy, fund size, LP commitment, called %, NAV as of reporting date, unfunded commitment, DPI, TVPI, and RVPI. 2. **Classify each fund by J-curve position.** - *Early (0–3 yrs)*: Predominantly unfunded; NAV reflects cost or slight markdowns. Discount typically 15–40% of NAV depending on strategy and GP track record. - *Mid-life (3–7 yrs)*: Active value creation period; NAV reflects marked-up assets. Discount range narrows to 0–20% for top-quartile GPs; wider for lower-quartile. - *Mature/Tail (7+ yrs)*: Harvesting phase; NAV concentrated in fewer holdings. Premium possible for near-term exit visibility; discount for stale or hard-to-exit assets. 3. **Apply strategy-specific discount/premium adjustments.** - Buyout: Anchor to public comparable EV/EBITDA multiples vs. GP marks; adjust for leverage and sector mix. - Venture/Growth: Haircut unrealized markups on late-stage private rounds; cross-check against recent public listing comps. Wider discount bands typical (20–50% for early-stage venture). - Credit/Real Assets: Assess yield-to-maturity and current income; narrower discount ranges where cash flows are contractual. - [VERIFY: confirm current secondary market clearing spreads by strategy from latest broker reports] 4. **Price unfunded commitments separately.** Unfunded obligations represent a future capital call liability. Value them as: `Unfunded × (1 − expected loss ratio)` discounted at buyer's required return, or apply a fixed cent-on-the-dollar rate consistent with market convention (often 0–5% cost for high-quality GPs, higher for lower-conviction names). 5. **Calculate fund-level bid prices.** For each fund: `Bid Price = (NAV × Discount/Premium Factor) − (Unfunded Commitment Cost)`. Express as % of NAV and as absolute dollar value. 6. **Aggregate to portfolio-level pricing.** - Sum fund-level bid prices for total portfolio value. - Calculate blended portfolio discount to NAV. - Compute portfolio-level expected return metrics (IRR, MOIC) using projected cash flow scenarios. - Assess concentration risk: top-5 fund exposure, single-GP exposure, strategy tilt, vintage clustering. 7. **Run sensitivity analysis.** Stress-test portfolio pricing across: - NAV adjustment scenarios (−10%, base, +10%) - Exit timing delays (6-month, 12-month pushback) - Public market drawdown impact on unrealized marks - Unfunded call pace acceleration ## Output Produce a **Portfolio Pricing Summary** containing: - **Portfolio overview table**: Fund name, vintage, strategy, NAV, unfunded, DPI/TVPI, J-curve stage, fund-level bid (% of NAV and $) - **Blended pricing**: Aggregate bid as % of total NAV, total dollar bid, weighted-average discount - **Return projections**: Base-case IRR and MOIC with stated assumptions on exit timing and pacing - **Sensitivity matrix**: Pricing across NAV adjustment and exit delay scenarios - **Key risk flags**: Concentration issues, stale NAVs (>6 months old), GP-specific concerns, large unfunded exposure - **Recommendation**: Suggested bid range with rationale tied to fund-level analysis ## Quality Checks - Confirm NAV dates are within acceptable staleness window (typically ≤2 quarters); flag older marks with [VERIFY] - Cross-check fund-level TVPI/DPI against benchmark databases (Cambridge Associates, Preqin, Burgiss) [VERIFY: confirm benchmark data access] - Validate that discount/premium assumptions align with recent comparable secondary transactions - Ensure unfunded commitment treatment is internally consistent across all funds - Verify arithmetic: fund-level bids must sum to portfolio-level total; IRR/MOIC models must tie to cash flow inputs - Confirm strategy classification matches GP-reported strategy (e.g., don't classify a growth equity fund as buyout) - Flag any fund where GP-reported NAV diverges >20% from implied public market equivalent