analyzing-manager-selection
Evaluates and selects investment managers with quantitative screening and qualitative assessment. Use when selecting fund managers, conducting manager due diligence, or evaluating strategy fit.
Best use case
analyzing-manager-selection is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Evaluates and selects investment managers with quantitative screening and qualitative assessment. Use when selecting fund managers, conducting manager due diligence, or evaluating strategy fit.
Teams using analyzing-manager-selection 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/analyzing-manager-selection/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How analyzing-manager-selection Compares
| Feature / Agent | analyzing-manager-selection | 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 and selects investment managers with quantitative screening and qualitative assessment. Use when selecting fund managers, conducting manager due diligence, or evaluating strategy fit.
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
# Analyzing Manager Selection ## When To Use - Screening new investment managers for inclusion in a portfolio or platform - Conducting periodic re-evaluation of existing manager relationships - Comparing managers within the same asset class or strategy mandate - Performing due diligence ahead of a fund commitment or allocation change - Assessing whether a manager's style drift, personnel turnover, or performance degradation warrants replacement ## Inputs To Gather - **Mandate definition**: Asset class, strategy type (e.g., long/short equity, core fixed income, venture), target geography, and any ESG or thematic constraints - **Quantitative data**: Returns (gross and net), AUM history, inception date, benchmark used, fee schedule (management fee, carry/incentive, hurdle rate) - **Risk metrics**: Standard deviation, Sharpe ratio, Sortino ratio, max drawdown, beta, tracking error, information ratio, up/down capture ratios - **Peer universe**: Comparable manager set or index for relative ranking - **Qualitative materials**: Pitch book or DDQ, organizational chart, key person bios, investment process narrative, operational due diligence reports - **Reference checks**: Prior or current allocator references, if available - **Existing portfolio context**: Current manager lineup, target allocation, overlap analysis inputs ## Workflow 1. **Define the search criteria** - Confirm asset class, strategy, geography, vehicle type (SMA, commingled fund, LP interest), and size constraints - Establish minimum track record length (typically 3–5 years; [VERIFY] against client IPS or committee policy) - Set quantitative screening thresholds (e.g., top-quartile returns over trailing 5 years, Sharpe > 0.5, max drawdown < 20%) 2. **Run quantitative screening** - Pull performance data across common periods (1Y, 3Y, 5Y, since inception) against the stated benchmark - Calculate risk-adjusted metrics: Sharpe, Sortino, information ratio, up/down capture - Flag managers with AUM growth > 50% in a single year (capacity risk) or AUM decline > 30% (redemption risk) - Rank candidates within peer universe; eliminate those below threshold on more than one key metric 3. **Conduct qualitative assessment** - **People**: Evaluate team stability (key person tenure, turnover rate), depth of analyst bench, succession planning, alignment of interest (co-investment, deferred comp) - **Process**: Assess repeatability of the investment process — idea generation, portfolio construction, position sizing, sell discipline - **Philosophy**: Confirm the stated philosophy matches observed portfolio behavior (e.g., a "value" manager should show consistent value factor exposure) - **Organization**: Review firm ownership structure, business concentration risk (single-strategy vs. diversified), regulatory history, compliance infrastructure 4. **Evaluate operational infrastructure** - Review custodian, administrator, auditor, and legal counsel independence - Assess valuation policy, especially for illiquid or hard-to-value holdings [VERIFY] - Check for any material findings in SOC 1 / SSAE 18 reports - Confirm insurance coverage (E&O, fidelity bond) adequacy relative to AUM 5. **Perform fee and terms analysis** - Compare management fees, incentive fees, hurdle rates, and clawback provisions against peer norms - Model net-of-fee return impact across scenarios (base, upside, downside) - Evaluate liquidity terms: lockup period, redemption notice, gate provisions [VERIFY] 6. **Score and rank finalists** - Apply a weighted scorecard across quantitative (typically 40–50%), qualitative (30–40%), and operational (15–20%) dimensions - Highlight any single-factor disqualifiers (regulatory action, key person departure, style drift beyond tolerance) - Prepare a side-by-side comparison matrix for the top 2–4 candidates 7. **Document recommendation** - Summarize the rationale for the recommended manager(s) with explicit reference to scorecard results - Note any conditions or monitoring triggers (e.g., "recommend allocation contingent on completion of on-site visit") - Include dissenting considerations or risks that the investment committee should weigh ## Output - **Manager Selection Memo**: 3–5 page narrative covering search parameters, screening methodology, finalist profiles, scorecard results, and final recommendation - **Comparison Matrix**: Side-by-side table of finalists across key quantitative, qualitative, and operational dimensions - **Scorecard Summary**: Weighted scoring grid with category scores, weights, and composite rank - **Risk Flag Register**: List of any amber or red flags identified during screening, with mitigation notes - **Monitoring Plan**: Suggested ongoing review triggers (performance breach, key person change, AUM threshold, regulatory event) ## Quality Checks - Confirm all return data uses the same calculation methodology (time-weighted vs. money-weighted) and fee basis (gross vs. net) across managers - Verify benchmark alignment — each manager should be measured against the benchmark stated in their own materials, not a generic proxy - Ensure the peer universe is appropriately constructed (same strategy, similar AUM band, comparable vintage) - Check that qualitative assessments cite specific evidence (e.g., "PM tenure of 12 years" not just "experienced team") - Validate that fee comparisons reflect the actual share class or negotiated terms, not headline rates [VERIFY] - Confirm no conflicts of interest exist (revenue-sharing, placement agent fees, affiliated relationships) or that they are disclosed - Flag any data gaps with [VERIFY] rather than interpolating or assuming
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