analyzing-proxy-contest-dynamics
Evaluates proxy fight mechanics with shareholder base analysis, ISS/Glass Lewis recommendations, and vote probability modeling. Use when analyzing proxy contests, assessing vote outcomes, or evaluating director nomination campaigns.
Best use case
analyzing-proxy-contest-dynamics is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Evaluates proxy fight mechanics with shareholder base analysis, ISS/Glass Lewis recommendations, and vote probability modeling. Use when analyzing proxy contests, assessing vote outcomes, or evaluating director nomination campaigns.
Teams using analyzing-proxy-contest-dynamics 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-proxy-contest-dynamics/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How analyzing-proxy-contest-dynamics Compares
| Feature / Agent | analyzing-proxy-contest-dynamics | 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 proxy fight mechanics with shareholder base analysis, ISS/Glass Lewis recommendations, and vote probability modeling. Use when analyzing proxy contests, assessing vote outcomes, or evaluating director nomination campaigns.
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 Proxy Contest Dynamics Evaluates proxy fight mechanics with shareholder base analysis, ISS/Glass Lewis recommendations, and vote probability modeling. ## When To Use - An activist has filed a DFAN14A or preliminary proxy statement nominating competing directors - Evaluating probability of success for a dissident slate before committing capital - Assessing whether management will settle or fight through to a shareholder vote - Modeling vote outcomes for event-driven positions (merger arbitrage with contested votes, activist long/short) - Reviewing a universal proxy card scenario and its impact on vote splitting ## Inputs To Gather - **Proxy filings**: DEFC14A (management), DFAN14A/PREC14A (dissident), and any amendments - **Shareholder base composition**: 13F filings for top holders, beneficial ownership breakdown (index funds, active managers, retail, insiders) - **Voting standard**: Plurality vs. majority voting; any advance-notice bylaw provisions [VERIFY — varies by company charter and state of incorporation] - **Historical voting data**: Prior annual meeting vote results (DEF 14A Item 5), particularly director support levels and say-on-pay outcomes - **ISS and Glass Lewis reports** (if available) or estimated recommendation based on policy guidelines - **Activist's track record**: Prior campaign win rates, settlement frequency, board seat gains - **Company-specific context**: Stock performance, governance scores, recent strategic actions, poison pill status [VERIFY — check for any newly adopted rights plan] ## Workflow 1. **Map the shareholder base into voting blocs** - Index/passive (BlackRock, Vanguard, State Street): Model using ISS/GL alignment tendencies — passives vote with ISS ~80-90% of the time on contested elections [VERIFY — current ISS voting statistics] - Dedicated active holders: Analyze stated positions, 13D/13G filings, prior voting behavior on activist campaigns - Hedge fund / event-driven holders: Check 13F turnover; recent accumulations suggest activist-sympathetic positioning - Retail: Estimate retail share (~10-30% of float typical); retail participation rates are low (~30% turnout) and tend to favor management unless strong media narrative exists - Insiders and affiliates: Identify locked-in management votes from insider holdings and employee plans 2. **Assess the dissident's case strength** - Underperformance: Compare TSR against peers and index over 1/3/5-year periods — quantify the performance gap - Governance deficiencies: Board tenure, independence, overboarding, compensation misalignment - Strategic thesis: Evaluate whether the activist's proposed changes (capital allocation, M&A, operational improvements) are credible and specific - Nominee quality: Assess dissident slate credentials versus incumbent directors 3. **Model ISS/Glass Lewis recommendations** - ISS tends to support dissidents when there is clear underperformance + governance concerns; apply the ISS framework: performance, responsiveness, dissident plan credibility, nominee quality - Glass Lewis weighs board refreshment and strategic rationale more heavily - Estimate recommendation probability: strong dissident case (>70% ISS support likelihood), mixed (40-60%), weak (<30%) 4. **Build the vote probability model** - Assign each shareholder bloc an estimated vote direction (management / dissident / proportional split) and turnout rate - Weight by share count to produce a base-case vote estimate - Run sensitivity scenarios: (a) ISS supports dissident, (b) ISS supports management, (c) partial slate recommendation - Under universal proxy rules, model vote splitting — shareholders can mix-and-match candidates across cards, which typically benefits stronger individual nominees regardless of slate 5. **Evaluate settlement probability** - Activists settle ~60-70% of campaigns before a vote [VERIFY — current settlement rate data] - Higher settlement likelihood when: ISS recommends dissident, vote model shows >45% dissident support, company faces reputational pressure - Assess company's defensive posture: advance-notice deadlines, rights plans, bylaw amendments, litigation against the activist 6. **Synthesize position implications** - For activist longs: Quantify expected value across outcomes (settlement with board seats, full vote win, vote loss) - For event-driven: Identify catalyst timeline (record date, proxy mailing, vote date) and map to position sizing - Flag any regulatory constraints: HSR thresholds, Section 13(d) group formation risk, industry-specific ownership limits [VERIFY] ## Output - **Shareholder Base Map**: Table of top 20+ holders with estimated voting direction, confidence level, and share counts - **Vote Probability Matrix**: Base case, bull case (ISS + GL support), and bear case (management sweep) with percentage outcomes for each nominee - **ISS/GL Recommendation Forecast**: Predicted recommendation with supporting rationale and key swing factors - **Settlement Probability Assessment**: Estimated likelihood of pre-vote settlement and expected terms (number of board seats, strategic concessions) - **Timeline and Catalyst Calendar**: Key dates from record date through annual meeting with decision points - **Risk Factors**: Scenarios that would materially change the outcome (poison pill adoption, competing offer, activist capitulation) ## Quality Checks - Shareholder bloc percentages must sum to ~100% of outstanding shares (allow for float estimation variance) - Vote model outputs should be stress-tested: flip the ISS recommendation and confirm the model produces meaningfully different results - Cross-check activist's 13D ownership against the vote model — the activist's own shares are a floor for dissident support - Verify voting standard is correctly applied (plurality: most votes wins; majority: >50% required — majority voting with resignation policies changes the dynamic significantly) [VERIFY] - Confirm proxy filing dates and deadlines against SEC EDGAR — stale filings invalidate the analysis - Flag any assumptions about retail turnout or passive fund voting behavior as estimates with stated confidence ranges