conducting-manager-track-record-analysis
Assesses GP track records for secondary pricing with fund-level attribution, unrealized portfolio assessment, and consistency analysis. Use when evaluating GP track records, analyzing fund performance consistency, or assessing manager quality.
Best use case
conducting-manager-track-record-analysis is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Assesses GP track records for secondary pricing with fund-level attribution, unrealized portfolio assessment, and consistency analysis. Use when evaluating GP track records, analyzing fund performance consistency, or assessing manager quality.
Teams using conducting-manager-track-record-analysis 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/conducting-manager-track-record-analysis/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How conducting-manager-track-record-analysis Compares
| Feature / Agent | conducting-manager-track-record-analysis | 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?
Assesses GP track records for secondary pricing with fund-level attribution, unrealized portfolio assessment, and consistency analysis. Use when evaluating GP track records, analyzing fund performance consistency, or assessing manager quality.
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
# Conducting Manager Track Record Analysis Assesses GP track records for secondary pricing with fund-level attribution, unrealized portfolio assessment, and consistency analysis. ## When To Use - Pricing an LP secondary interest and need to evaluate the underlying GP's performance history - Conducting diligence on a GP-led continuation vehicle or tender offer - Comparing multiple managers across a portfolio for LP portfolio optimization - Assessing whether a GP's unrealized book is credible relative to historical realizations - Building conviction (or flagging risk) around a GP's ability to generate returns in current and future funds ## Inputs To Gather - **Fund-level performance data**: Net IRR, net TVPI, DPI, and RVPI for each fund vintage, ideally quarterly - **Cash flow history**: Capital call and distribution schedules per fund (used for PME and J-curve analysis) - **Portfolio company detail**: Entry dates, entry multiples, current carrying values, sector, and geography - **Benchmark data**: Cambridge Associates, Burgiss, or Preqin quartile rankings by vintage and strategy - **GP-provided materials**: PPMs, annual letters, AGM presentations, prior fund tearsheets - **Organizational info**: Team tenure, key-person provisions, GP commitment levels, succession plans - **Market context**: Relevant sector indices and M&A multiples for the deployment periods in question ## Workflow 1. **Build the fund-by-fund performance table** - Tabulate net IRR, TVPI, DPI, RVPI for each fund vintage - Note the as-of date and whether figures are audited or estimated - Flag any restated or reclassified NAVs [VERIFY against audited financials] 2. **Quartile-rank each fund against vintage-year peers** - Use at least one recognized benchmark (Cambridge, Burgiss, Preqin) - Distinguish between gross and net rankings — secondary pricing relies on net returns - Assess whether top-quartile claims hold across multiple benchmark providers [VERIFY benchmark vintage cutoffs] 3. **Analyze DPI progression and realization patterns** - Plot DPI over time for each fund to assess pace of capital return - Compare DPI at equivalent fund ages across vintages — is the GP accelerating or slowing distributions? - Identify funds where TVPI is high but DPI is low (concentration of value in unrealized holdings) 4. **Decompose fund-level returns by deal attribution** - Identify top 3–5 contributors and detractors per fund by gross MOIC - Calculate loss ratios (percentage of invested capital in deals below 1.0x) - Determine whether returns are driven by a single outlier or distributed across the portfolio - Flag repeat sector or geographic bets that inflate apparent diversification 5. **Stress-test unrealized portfolio** - Compare carrying values to public-market comparables and recent transaction multiples - Apply haircuts to positions held above entry multiple for >3 years without a realization event - Assess revenue/EBITDA growth in underlying companies relative to the marks being applied - Score each material unrealized holding as: conservatively marked / fairly marked / aggressively marked 6. **Evaluate consistency across fund cycles** - Determine whether the GP has maintained strategy discipline (check size, sector focus, hold period) - Flag style drift — e.g., a lower-middle-market buyout fund doing growth equity or larger deals - Assess team continuity: have the same senior partners been responsible for the realized track record? - Note any key-person departures and whether they coincided with performance changes 7. **Synthesize into a manager quality score or narrative** - Summarize realized vs. unrealized performance split - State whether the GP is a repeat top-quartile performer, a median manager, or inconsistent - Highlight the 2–3 strongest positives and 2–3 key risks for secondary pricing purposes - Recommend a NAV discount or premium adjustment supported by the analysis ## Output A structured track record memorandum containing: - **Performance summary table**: Fund-by-fund net IRR, TVPI, DPI, RVPI with quartile rankings - **Attribution analysis**: Top/bottom deals per fund, loss ratios, concentration metrics - **Unrealized portfolio assessment**: Marking credibility scores, key holdings, and haircut recommendations - **Consistency analysis**: Strategy adherence, team stability, cross-vintage performance trends - **Pricing implications**: Recommended NAV adjustment range (discount or premium) with supporting rationale - **Risk flags**: Itemized list of concerns (e.g., key-person risk, concentrated unrealized book, style drift) ## Quality Checks - Every net IRR and TVPI figure traces to a sourced document (GP report, audited statement, or data provider) - Quartile rankings are dated and benchmark-provider-specific — do not blend providers - Unrealized marks are cross-referenced against at least one external valuation indicator - Loss ratios are calculated on invested capital, not committed capital - Any performance figures predating the current team or strategy are clearly segregated - [VERIFY] vintage year classifications match the benchmark provider's definition (first close vs. first draw) - [VERIFY] GP-reported net returns are net of management fees, carried interest, and fund-level expenses - Analysis distinguishes between flagship strategy performance and ancillary/co-investment vehicles
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