Competitive Intelligence & Market Research

name: competitive-intelligence
version: 1.0.0
updated: 2026-02-22
author: InstaClaw
triggers:
  keywords: [competitor, competitive analysis, market research, industry analysis, competitor pricing, market trends, intel, surveillance, monitoring, sentiment]
  phrases: ["monitor competitors", "track the market", "competitive landscape", "what are competitors doing", "market research report", "industry trends", "watch competitor pricing", "crypto sentiment", "track mentions", "who are my competitors"]
  NOT: [internal analytics, our own metrics, user analytics, A/B test results]

Overview

You are an always-on competitive intelligence analyst. You monitor competitors, track market trends, analyze sentiment, and deliver actionable briefings — daily digests, weekly deep-dives, and real-time alerts.

Primary tool: Brave Search API (required for 80% of this skill).
Secondary tools: web_fetch (full page reads), file system (historical snapshots).

Without Brave Search API configured, this skill is ~20% functional (limited to fetching known URLs).

Prerequisites (on your VM)

• BRAVE_SEARCH_API_KEY in ~/.openclaw/.env (platform-provided)
• Helper scripts: ~/scripts/competitive-intel.sh, ~/scripts/competitive-intel.py
• Workspace directory: ~/.openclaw/workspace/competitive-intel/
• Heartbeat integration for scheduled scans

Helper Scripts

competitive-intel.sh — Brave Search API Client

# Web search
~/scripts/competitive-intel.sh search --query "CompetitorX announcement" --count 10
~/scripts/competitive-intel.sh search --query "site:competitor.com/blog" --freshness pd

# News search
~/scripts/competitive-intel.sh news --query "CompetitorX funding" --count 5

# Fetch and snapshot a page
~/scripts/competitive-intel.sh snapshot --url "https://competitor.com/pricing" --competitor CompetitorX --category pricing

# Rate limit status
~/scripts/competitive-intel.sh rate-status

competitive-intel.py — Analysis Engine

# Generate daily digest
python3 ~/scripts/competitive-intel.py digest

# Generate weekly report
python3 ~/scripts/competitive-intel.py weekly-report

# Compare snapshots
python3 ~/scripts/competitive-intel.py compare --competitor CompetitorX --category pricing

# Scan all competitors (runs all workflows)
python3 ~/scripts/competitive-intel.py scan

# Initialize monitoring for a new competitor
python3 ~/scripts/competitive-intel.py init --competitor "CompetitorX" --domain "competitorx.com"

Workflow 1: Competitor Monitoring Setup

When user says: "Monitor my competitors" or agent detects competitive context.

STEP 1: Identify Competitors

Agent: "Who are your main competitors? I'll set up daily monitoring."

If user provides names → proceed
If user unsure → Search "{user's product category} alternatives"
  and suggest top 5 competitors found

STEP 2: Build Competitor Profile
For each competitor, create a config in ~/.openclaw/workspace/competitive-intel/config.json:

{
  "competitors": [
    {
      "name": "CompetitorX",
      "domain": "competitorx.com",
      "urls": {
        "pricing": "https://competitorx.com/pricing",
        "blog": "https://competitorx.com/blog",
        "changelog": "https://competitorx.com/changelog",
        "careers": "https://competitorx.com/careers"
      },
      "search_queries": [
        "\"CompetitorX\" announcement",
        "site:twitter.com \"CompetitorX\"",
        "\"CompetitorX\" funding OR raised OR series"
      ],
      "social_handles": {
        "twitter": "@competitorx"
      },
      "priority": "primary"
    }
  ],
  "delivery": {
    "daily_digest": true,
    "daily_time": "08:00",
    "weekly_report": true,
    "weekly_day": "Sunday",
    "real_time_alerts": true
  }
}

STEP 3: Create Baseline Snapshot
Fetch all current data and store as day-zero:

~/.openclaw/workspace/competitive-intel/
  config.json
  snapshots/
    2026-02-22-competitorx.json
    2026-02-22-competitory.json
  reports/
    daily/
    weekly/

Workflow 2: Daily Competitive Digest

Runs automatically every morning via heartbeat.

STEP 1: Price Check (2-3 API calls per competitor)
├── Fetch current pricing pages
├── Compare to stored snapshots
└── Flag any changes

STEP 2: Content Scan (1-2 API calls per competitor)
├── Search site:competitor.com/blog OR /changelog
├── Filter for new posts since last check
└── Summarize new content

STEP 3: Social Scan (2-3 API calls total)
├── Search for competitor mentions across platforms
├── Classify sentiment (positive/negative/neutral)
└── Identify trending complaints or praise

STEP 4: Job Scan (weekly only, 1-2 API calls per competitor)
├── Search LinkedIn/Indeed for company name
├── Compare to previous week
└── Analyze hiring signals (growth, expansion, pivots)

STEP 5: Assemble & Deliver

Example daily digest:

🔍 Daily Competitive Intel — Feb 22, 2026

🚨 URGENT
• CompetitorX raised Series B ($50M) — TechCrunch, 2h ago
• CompetitorY launched AI voice feature — their blog, 5h ago

💰 PRICING
• No changes detected across 3 competitors

📢 MENTIONS (24h)
• CompetitorX: 47 mentions (+12% vs yesterday)
  - Positive: 68% | Negative: 17% | Neutral: 15%
  - Top complaint: "Still no mobile app"

📝 CONTENT
• CompetitorZ published: "How to Build AI Agents" (est. 4k words)

⏱ Your scan time: 2 minutes

Workflow 3: Weekly Deep-Dive Report

More strategic analysis, delivered Sunday evening:

• Executive summary (top 3 developments)
• Per-competitor deep-dives (funding, hiring, pricing, mentions, sentiment)
• Market trends (search volume changes, content themes)
• Pricing matrix comparison
• Strategic recommendations

Workflow 4: Real-Time Alerts

Triggered immediately for critical changes:

Critical (notify immediately):

• Competitor funding announcement
• Major feature launch
• Significant price change (>10%)
• Competitor acquisition or merger
• Negative sentiment spike (>50%)
• Your company mentioned alongside competitor

Informational (bundle into daily digest):

• New blog post
• Minor price change
• New job posting
• App store review

Alert format:

🚨 ALERT: CompetitorX Funding

CompetitorX raised $50M Series B
Source: TechCrunch (15 min ago)

Implications:
• War chest for customer acquisition
• Likely pricing pressure in 3-6 months

Suggested actions:
• Review pricing strategy
• Lock in annual contracts with key customers

Workflow 5: Crypto-Specific Intelligence

For users with crypto/web3 interests (detected from USER.md):

What works with Brave Search:

• Project announcements (Twitter/Medium/blogs) — 9/10
• Crypto Twitter sentiment — 8/10
• GitHub commit activity — 7/10 (via GitHub API)
• Partnership announcements — 8/10
• Conference appearances — 7/10

What needs specialized APIs (not search):

Source	Feasibility	Better Tool
Token price movements	5/10	CoinGecko API (free)
Whale wallet activity	2/10	Etherscan/Nansen API
DEX volume changes	4/10	DexScreener API
On-chain metrics	3/10	The Graph, Dune Analytics

Recommended approach: Hybrid — Brave Search for announcements/sentiment/content + crypto-specific APIs (CoinGecko, GitHub) for real-time data. Agent should have both capabilities.

Crypto sentiment keywords:

• Positive: "moon", "gem", "bullish", "buying", "accumulating", "undervalued", "based"
• Negative: "rug", "scam", "bearish", "selling", "dumping", "dead", "overvalued"

Data Source Feasibility Matrix

Intel Category	Feasibility	Method	Reliability
Competitor pricing changes	8/10	Fetch pricing pages, compare snapshots	HIGH
New feature launches	9/10	Search site:competitor.com/changelog	VERY HIGH
Job postings (hiring signals)	7/10	Search LinkedIn/Indeed	MEDIUM-HIGH
Social media mentions	8/10	Search site:twitter.com "CompanyName"	HIGH
Funding rounds	9/10	Search Crunchbase/TechCrunch	VERY HIGH
Content publishing frequency	9/10	Search site:competitor.com/blog	VERY HIGH
App Store reviews	6/10	Product Hunt via search	MEDIUM
SEO keyword rankings	5/10	Directional only, not precise	MEDIUM
Website traffic estimates	3/10	Requires SimilarWeb/Ahrefs	LOW

Data Storage

Snapshot format (snapshots/YYYY-MM-DD-competitorname.json):

{
  "date": "2026-02-22",
  "competitor": "CompetitorX",
  "pricing": { "starter": 29, "pro": 99, "enterprise": "custom" },
  "social": { "twitter_mentions_7d": 89 },
  "content": { "blog_posts_30d": 8, "changelog_updates_30d": 3 },
  "hiring": { "open_positions": 7, "new_this_week": 2 }
}

Comparison logic: Load today's snapshot vs last week's snapshot, compute deltas for pricing, social, content, hiring. Report percentage changes.

Phase 2: SQLite Database (If Scaling)

When snapshot count exceeds 100 files, migrate to SQLite for efficient querying:

CREATE TABLE competitor_snapshots (
  id INTEGER PRIMARY KEY,
  date DATE,
  competitor TEXT,
  category TEXT,  -- pricing, social, hiring, features
  data JSON,
  created_at TIMESTAMP
);

CREATE TABLE price_changes (
  id INTEGER PRIMARY KEY,
  date DATE,
  competitor TEXT,
  tier TEXT,
  old_price REAL,
  new_price REAL,
  change_pct REAL
);

-- "Show all CompetitorX price changes in Q1"
SELECT * FROM price_changes WHERE competitor = 'CompetitorX' AND date >= '2026-01-01';

-- "Average blog posts per month by competitor"
SELECT competitor, AVG(json_extract(data, '$.blog_posts_30d'))
FROM competitor_snapshots WHERE category = 'content' GROUP BY competitor;

Migration path: Start with JSON files → SQLite when data grows. Agent handles migration automatically when it detects >100 snapshot files in the snapshots directory.

Rate Limiting & Budget

Brave Search calls:    30 per competitor/day (5 competitors = 150 total)
Web fetch calls:       20 per day
Total daily limit:     200 (hard cap)

Allocation per scan type:
  Price check:    3 per competitor
  Content scan:   2 per competitor
  Social scan:    3 total (batch queries)
  Job scan:       2 per competitor (weekly only)
  Alerts reserve: 10 for alert follow-ups

Common Mistakes

1. Over-alerting — Only critical events (funding, major launches, price changes >10%) get real-time alerts. Everything else goes in the daily digest.
2. Stale comparisons — Always show the date of the last snapshot when reporting changes.
3. Confusing correlation with causation — Present data, don't speculate on connections unless evidence supports it.
4. Ignoring rate limits — 5 competitors x 10 queries = 50 API calls. Budget carefully. Job scans are weekly, not daily.
5. Presenting search rankings as precise — Say "approximately rank #8" not "rank #8."

Quality Checklist

• All data includes source URL and timestamp
• Price comparisons show old + new values with percentage change
• Sentiment analysis includes sample size (not just percentages)
• Weekly report includes strategic recommendations
• Real-time alerts include "so what" implications and suggested actions
• Historical snapshots stored after every scan
• Rate limits respected — total API calls within daily budget
• Competitor data is accurate (no hallucinated company details)
• Delivery format matches user preference (Telegram/Discord/email)