---
name: "Competitor intel"
repo: https://github.com/ognjengt/founder-skills
source: https://github.com/ognjengt/founder-skills/blob/HEAD/skills/competitor-intel/SKILL.md
license: "MIT"
install: "npx skills add ognjengt/founder-skills --skill competitor-intel"
page: https://100xlab.com/resources/agent-skills/ognjengt-founder-skills--competitor-intel--1mngmxn
---

# Competitor Intel

## Purpose
Provide data-backed competitive intelligence by researching real signals across the web—no assumptions, no made-up numbers.

---

## Execution Logic

**Check $ARGUMENTS first to determine execution mode:**

### If $ARGUMENTS is empty or not provided:
Respond with:
"competitor-intel loaded, proceed with competitor name and any context (website, industry, etc.)"

Then wait for the user to provide their requirements in the next message.

### If $ARGUMENTS contains content:
Proceed immediately to Task Execution (skip the "loaded" message).

---

## Task Execution

When user requirements are available (either from initial $ARGUMENTS or follow-up message):

### 1. Check for Business Context (Optional)
Check if `FOUNDER_CONTEXT.md` exists in the project root.
- **If it exists:** Read it to understand your company's positioning, strengths, and goals—this informs the leverage strategies.
- **If it doesn't exist:** Proceed with analysis focused purely on competitor weaknesses.

### 2. Extract Input
From the user's requirements, extract:
- Competitor name (required)
- Competitor website (if provided)
- Industry/vertical (if provided)
- Specific areas of interest (if provided)

### 3. Research Phase — MANDATORY WEB SEARCH
**This skill REQUIRES web search. Do not proceed without searching.**

Execute web searches across these sources:

#### Business Metrics Research
Search for verified data only. Query patterns:
- `"[Competitor]" revenue OR MRR OR ARR site:crunchbase.com`
- `"[Competitor]" funding raised valuation site:crunchbase.com`
- `"[Competitor]" employees headcount site:linkedin.com`
- `"[Competitor]" revenue growth OR metrics`
- `"[Competitor]" pricing customers`
- `"[Competitor]" CEO OR founder interview revenue`
- `"[Competitor]" Series A OR Series B OR funding`

#### Traffic & SEO Research
Search for web traffic and search presence signals:
- `"[Competitor]" site:similarweb.com` (traffic estimates, top pages, traffic sources)
- `"[Competitor]" site:ahrefs.com` (backlinks, domain rating, organic keywords)
- `"[Competitor]" site:semrush.com` (traffic, keyword rankings, ad spend)
- `"[Competitor]" site:trends.google.com` (search interest over time)
- `[Competitor website domain] site:builtwith.com` (tech stack, tools used)

#### Technical & Product Research
Search for product and development signals:
- `"[Competitor]" site:github.com` (open source activity, tech stack, hiring signals)
- `[Competitor GitHub org]` (commit frequency, contributors, project activity)
- `"[Competitor]" API OR integration OR developer`

#### Advertising Research
Search for ad strategy and spend signals:
- Search Meta Ads Library: `https://www.facebook.com/ads/library/` for [Competitor]
- `"[Competitor]" ads site:facebook.com/ads/library`
- `"[Competitor]" advertising spend OR ad budget`
- `"[Competitor]" marketing campaign`

#### Weakness & Sentiment Research
Search for complaints, issues, and struggles:
- `"[Competitor]" reviews site:g2.com`
- `"[Competitor]" reviews site:capterra.com`
- `"[Competitor]" reviews site:trustpilot.com`
- `"[Competitor]" complaints OR issues OR problems`
- `"[Competitor]" "doesn't work" OR "broken" OR "terrible"`
- `"[Competitor]" layoffs OR firing OR cuts`
- `"[Competitor]" lawsuit OR sued`

#### Signal Research (for predictions)
Search for hiring, product, and strategic signals:
- `"[Competitor]" hiring site:linkedin.com`
- `"[Competitor]" job openings`
- `"[Competitor]" new feature OR launch OR release`
- `"[Competitor]" roadmap OR upcoming`
- `"[Competitor]" partnership OR integration`
- `"[Competitor]" site:twitter.com OR site:x.com` (founder/company posts)

### 4. Compile Verified Metrics
From research, extract ONLY verified numbers with sources:
- MRR/ARR (if disclosed)
- Funding raised (total and rounds)
- Valuation (if known)
- Employee count
- Customer count
- Churn rate (if disclosed)
- Growth rate (if disclosed)
- Pricing tiers

**CRITICAL RULE:** If a metric cannot be found with a source, mark it as "Not publicly available" — DO NOT estimate or assume.

### 5. Identify Leverage Opportunities
Analyze collected data to find 3 actionable weak spots:

Look for patterns in:
- **Product gaps**: Features users complain about, missing integrations
- **Service failures**: Support complaints, response times, bugs
- **Pricing friction**: Users complaining about cost, hidden fees, poor value
- **Trust issues**: Security concerns, data breaches, broken promises
- **Operational struggles**: Layoffs, leadership changes, funding difficulties
- **Marketing weaknesses**: Poor ad execution, weak positioning, low engagement

For each weakness, formulate an actionable strategy your company can execute.

### 6. Predict Next Moves
Based on all signals, predict what the competitor will likely do next:

Signals to interpret:
- **Hiring patterns**: Engineering = product push, Sales = growth mode, Support = scaling issues
- **Job postings**: Reveal technology bets, market expansion, new products
- **Funding status**: Recent raise = aggressive expansion, No raise in 2+ years = potential trouble
- **Content/PR**: Topics they're pushing indicate strategic focus
- **Partnership announcements**: Reveal market positioning and gaps
- **Founder activity**: Where they speak, what they post, who they meet

### 7. Format Output
Structure findings according to **Output Format** section.

---

## Writing Rules
Hard constraints. No interpretation.

### Core Rules
- Every metric MUST include a source link or be marked "Not publicly available"
- No estimations, assumptions, or "likely" numbers for metrics
- Strategies must be actionable (specific steps, not vague advice)
- Predictions must cite the signals that support them
- Use neutral, analytical tone—not competitive trash talk
- Date all findings (data freshness matters)

### Source Rules
- Prioritize primary sources (company announcements, founder interviews, SEC filings)
- Crunchbase, LinkedIn, G2, Capterra are acceptable secondary sources
- News articles are acceptable if they cite primary sources
- Avoid unverified Twitter/X claims unless from official company accounts

### Strategy Rules
- Each strategy must exploit a verified weakness
- Each strategy must include concrete next steps
- Strategies should be achievable within 30-90 days
- Avoid strategies that require significant capital unless user has it

---

## Output Format

```markdown
# Competitor Intel: [Competitor Name]
**Generated:** [Date]
**Sources searched:** [Count] sources across Crunchbase, LinkedIn, G2, Capterra, news, social

---

## 1. Verified Business Metrics

| Metric | Value | Source | Date |
|--------|-------|--------|------|
| Funding Raised | $X | [Source](url) | [Date] |
| Valuation | $X | [Source](url) | [Date] |
| Employee Count | X | [Source](url) | [Date] |
| MRR/ARR | Not publicly available | — | — |
| Customer Count | ~X | [Source](url) | [Date] |
| Churn Rate | Not publicly available | — | — |

**Key Observations:**
- [Insight about their financial health]
- [Insight about their growth trajectory]

---

## 2. Leverage Strategies

### Strategy 1: [Name]
**Weakness exploited:** [What you found]
**Evidence:** [Quote or data point with source]

**Action steps:**
1. [Specific action]
2. [Specific action]
3. [Specific action]

**Expected outcome:** [What this achieves]

---

### Strategy 2: [Name]
**Weakness exploited:** [What you found]
**Evidence:** [Quote or data point with source]

**Action steps:**
1. [Specific action]
2. [Specific action]
3. [Specific action]

**Expected outcome:** [What this achieves]

---

### Strategy 3: [Name]
**Weakness exploited:** [What you found]
**Evidence:** [Quote or data point with source]

**Action steps:**
1. [Specific action]
2. [Specific action]
3. [Specific action]

**Expected outcome:** [What this achieves]

---

## 3. Predicted Next Moves

### Prediction 1: [What they'll likely do]
**Confidence:** High/Medium/Low
**Supporting signals:**
- [Signal 1 with source]
- [Signal 2 with source]

**Implication for you:** [How to prepare/respond]

### Prediction 2: [What they'll likely do]
**Confidence:** High/Medium/Low
**Supporting signals:**
- [Signal 1 with source]
- [Signal 2 with source]

**Implication for you:** [How to prepare/respond]

---

## 4. Information Gaps
Metrics and data that could not be verified:
- [Item 1]
- [Item 2]

**Suggested next steps to fill gaps:**
- [How to find this information]
```

---

## Quality Checklist (Self-Verification)

Before finalizing, verify ALL of the following:

### Research Check
- [ ] I performed web searches (did not rely on training data alone)
- [ ] I searched Crunchbase, LinkedIn, G2/Capterra, and news sources
- [ ] I searched traffic/SEO sources (Similarweb, Ahrefs, Semrush, Google Trends)
- [ ] I checked BuiltWith for tech stack and GitHub for development signals
- [ ] I searched Meta Ads Library for advertising activity
- [ ] I searched for both positive and negative signals

### Metrics Check
- [ ] Every metric has a source URL or is marked "Not publicly available"
- [ ] No numbers are estimated or assumed
- [ ] Dates are included for data freshness

### Strategy Check
- [ ] All 3 strategies exploit verified weaknesses (not assumptions)
- [ ] Each strategy has concrete, actionable steps
- [ ] Strategies are realistic for a startup to execute

### Prediction Check
- [ ] Each prediction cites specific signals
- [ ] Confidence levels are honest (not all "High")
- [ ] Implications are actionable

### Output Check
- [ ] Output matches the Output Format exactly
- [ ] Tone is analytical, not inflammatory
- [ ] Information gaps are acknowledged

**If ANY check fails → revise before presenting.**

---

## Defaults & Assumptions

Use these unless overridden:
- Assume user is a startup founder analyzing a direct competitor
- Focus on actionable intelligence (not academic analysis)
- Prioritize recent data (< 12 months old)
- Default confidence for predictions: Medium (unless strong signals exist)
- If industry unknown, infer from competitor's website/positioning

Document any assumptions made in the output.

---