---
name: strategic-acquisition-target-screener
description: "Screens a list of potential acquisition targets against defined strategic and financial criteria — revenue size, growth rate, margin profile, capability fit, and geography — and returns a weighted scored and ranked shortlist with per-candidate strategic fit commentary, integration risk flags, and a recommended pursuit tier. Use when evaluating an acquisition pipeline, prioritizing inbound targets, or building a screened shortlist for an M&A thesis."
argument-hint: "[target-list] [strategic-criteria]"
allowed-tools: ["Read"]
---

# Strategic Acquisition Target Screener

## Purpose
Convert a raw list of potential acquisition targets into a defensible, weighted, and ranked shortlist — scoring each candidate against a defined strategic and financial rubric and adding fit commentary — so corporate development can focus diligence resources on the highest-conviction targets and defend the shortlist to an investment committee.

## When to Use
Invoke this skill when the user asks to:
- Screen or evaluate a list of potential acquisition targets
- Prioritize an M&A pipeline or inbound deal flow
- Build a ranked acquisition shortlist for an investment committee or board
- Score targets against a strategic thesis or acquisition criteria
- Compare multiple candidates on strategic and financial fit
- Filter a long list of companies down to a diligence-ready set

## Inputs Required
Before starting, collect:
- **Target list**: The candidate companies to screen — names plus whatever data is available (revenue, growth, margins, geography, product/capability)
- **Strategic rationale**: The thesis driving the M&A search (e.g., enter a new geography, acquire a capability, consolidate a category, add recurring revenue)
- **Strategic criteria and weights**: The dimensions that matter and their relative importance (capability fit, geography, customer overlap, technology, team)
- **Financial criteria**: Target ranges for revenue size, growth rate, and margin profile — plus any hard filters (minimum revenue, profitability requirement)
- **Deal constraints**: Approximate budget/valuation ceiling, structure preferences (majority vs. tuck-in), and integration capacity
- **Dealbreakers**: Absolute disqualifiers (e.g., no distressed assets, no companies below X% gross margin, no specific geographies)

If weights are not provided, apply a default balanced weighting (strategic fit 50%, financial profile 35%, integration feasibility 15%) and state the assumption. If data is missing for a candidate on a given criterion, score it as "Unknown / diligence required" rather than guessing.

## Instructions

### Step 1: Establish the Scoring Rubric
Before scoring any candidate, lock the rubric so scores are comparable:
- Convert each strategic and financial criterion into a **0–5 scale** with explicit anchors (e.g., Capability Fit: 5 = directly fills the named capability gap; 3 = adjacent/partial; 1 = tangential; 0 = irrelevant)
- Confirm the **weights** for each criterion; normalize so they sum to 100%
- Identify **hard filters** (dealbreakers) — any candidate failing one is flagged as disqualified regardless of weighted score
- Define the **financial bands** (revenue, growth, margin) as scoring anchors, not just pass/fail — a candidate slightly outside a range should lose points, not be eliminated, unless it's a stated hard filter

### Step 2: Apply Hard Filters First
Run every candidate through the dealbreaker filters. For each disqualified candidate, record the single specific reason (e.g., "Below $10M revenue floor," "In excluded geography — LATAM," "Sub-40% gross margin"). Disqualified candidates are set aside and reported separately, not scored on the full rubric.

### Step 3: Score Surviving Candidates Across Five Dimensions
For each remaining candidate, assign a 0–5 score with a one-line justification on each:

**1. Capability & Product Fit** — Does the target fill the specific gap in the thesis? Score against the named capability, not "good business overall."

**2. Financial Profile** — Composite of revenue size (scale relevance), growth rate (trajectory vs. target band), and margin profile (quality of earnings). Note where each sub-metric lands relative to the stated bands.

**3. Market & Geographic Fit** — Does the target extend reach into a priority geography, segment, or customer base? Score customer overlap (accretive vs. redundant) explicitly.

**4. Integration Feasibility** — Technology stack compatibility, cultural/operational similarity, size digestibility relative to the acquirer, and integration capacity. Larger and more complex targets score lower here.

**5. Strategic Optionality** — Does owning this target create follow-on moves, defensive value, or a platform for further roll-up? Distinguish one-time value from compounding value.

### Step 4: Calculate Weighted Scores and Rank
- Multiply each dimension score by its weight and sum to a **weighted composite (0–100 scale)**
- Rank all surviving candidates from highest to lowest
- Assign each candidate a **pursuit tier**:
  - **Tier 1 — Pursue Now**: composite ≥ 75, no critical unknowns
  - **Tier 2 — Develop / Diligence**: composite 55–74, or high score with key data gaps
  - **Tier 3 — Watch / Deprioritize**: composite 40–54
  - **Below 40 or disqualified**: pass, with reason

### Step 5: Write Per-Candidate Strategic Fit Commentary
For each Tier 1 and Tier 2 candidate, write 2–4 sentences covering:
- The single strongest reason to pursue (tied to the thesis)
- The most material risk or unknown (integration, valuation, data gap, competitive process)
- A recommended next action (e.g., "Initiate outreach," "Request financials before advancing," "Confirm customer overlap before valuing")

### Step 6: Produce the Shortlist Summary
Close with a portfolio-level read: how many candidates cleared each tier, whether the pipeline is deep enough to support the thesis, the top 3 targets in priority order, and any gap in the pipeline the search should be expanded to fill.

## Output Format
- **Structure**: Rubric summary → disqualified list → scored ranking table → per-candidate commentary → shortlist summary
- **Length**: 900–1,400 words, scaling with number of targets
- **Format**: A ranked scoring table (candidate, five dimension scores, weighted composite, tier) followed by structured commentary blocks
- **Sections**: Scoring Rubric & Weights → Disqualified Targets (with reasons) → Ranked Scoring Table → Strategic Fit Commentary (Tier 1 & 2) → Shortlist Summary & Recommendation
- **Tone**: Corporate development director — analytical, evidence-anchored, decisive; comfortable stating a recommendation and naming risks, not hedging

## Quality Checklist
Before delivering output, verify:
- [ ] Every candidate is accounted for — either scored, tiered, or explicitly disqualified with a stated reason
- [ ] Each dimension score has a one-line justification, not a bare number
- [ ] Weights are stated, sum to 100%, and are actually applied in the composite calculation
- [ ] The ranking table sorts candidates by weighted composite, highest to lowest
- [ ] Missing data is flagged as "diligence required" rather than silently assumed
- [ ] Every Tier 1 and Tier 2 candidate has commentary with a strongest reason, a key risk, and a next action
- [ ] The shortlist summary names the top 3 targets in explicit priority order

## Notes
- Integration feasibility is the most frequently underweighted dimension — a strategically perfect target that the acquirer cannot digest is a lower-conviction deal than the score alone suggests. Weight it deliberately.
- Where a candidate scores high but rests on unverified financials, place it in Tier 2 (diligence) rather than Tier 1 — the tier should reflect conviction, not just the raw number.
- Redundant customer overlap is often mistaken for synergy; a target whose customers you already own adds less strategic value than one that opens a net-new base. Score overlap as a distinct factor.
- This screen sizes and ranks a pipeline; it is not a valuation. Flag when the strongest strategic fit is likely to command a premium the deal constraints won't support.

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## How to use this skill

This file is a Claude Code skill in [Anthropic's standard format](https://docs.anthropic.com/en/docs/claude-code/skills) — markdown with YAML frontmatter at the top.

**Installing in Claude Code:**
- `~/.claude/skills/<folder-name>/SKILL.md` — auto-loads in every session anywhere on your machine (recommended for skills you'll use across multiple projects)
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Restart Claude Code or open a new session to register.

**Using in Claude.ai, ChatGPT, Gemini, or other AI tools:**

1. Drag this file into a new chat, or copy and paste its contents
2. Send your task or request as your next message — the AI will apply the skill where it fits

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