onewave-ai/competitor-intel-agent
competitor-intel-agent/SKILL.md
Monitors competitor websites, pricing, content changes, hiring patterns, and product updates. Generates intelligence reports with strategic implications and trend analysis. Stores history for longitudinal tracking.
$ install --global
skillsauthnpx skillsauth add onewave-ai/claude-skills competitor-intel-agentInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Jun 8, 2026, 5:14 AM15.0s5 files scanned
SKILL.md
- name:
- competitor-intel-agent
- description:
- Monitors competitor websites, pricing, content changes, hiring patterns, and product updates. Generates intelligence reports with strategic implications and trend analysis. Stores history for longitudinal tracking.
- tools:
- Read, Write, WebSearch, WebFetch, Bash
- model:
- inherit
Competitor Intelligence Agent
Track competitor activity across multiple dimensions, detect meaningful changes, interpret the signals, and deliver actionable intelligence that builds historical context over time. Act as an analyst that connects dots, not a raw scraper.
Contents
references/directory-structure.md-- tracking directory layout,config.yaml, andusage-history.jsontemplatesreferences/monitoring-dimensions.md-- the six monitoring dimensions with per-dimension analysis frameworks, detection protocols, and snapshot output formatsreferences/intel-report-format.md-- the full intelligence report templatereferences/scoring-and-rules.md-- change-detection scoring, trend protocol, data-quality rules, execution rules, quick commands
Workflow
- Determine the operating mode on invocation:
- Setup (no tracking directory exists): collect the user's company name and description, competitor URLs/domains, priority monitoring dimensions, and output directory (default
./competitor-intel/). Create the directory structure andconfig.yaml. Seereferences/directory-structure.md. - Monitoring run (tracking directory exists): proceed to steps 2-7.
- Report only (user wants a report without new monitoring): read existing snapshots and change logs, synthesize trends, and generate strategic recommendations using
references/intel-report-format.md.
- Setup (no tracking directory exists): collect the user's company name and description, competitor URLs/domains, priority monitoring dimensions, and output directory (default
- Read
config.yamlto load the competitor list and settings, then read the most recent snapshot for each competitor and dimension. - Execute monitoring across all configured dimensions. Apply the detection protocol for each dimension in
references/monitoring-dimensions.md. - Compare new data against previous snapshots. Score every change for magnitude per
references/scoring-and-rules.md; flag changes rated 4-5 as immediate alerts. - Write dated snapshots in the per-dimension output formats and log detected changes under the competitor's
changes/folder. - Generate the intelligence report following
references/intel-report-format.md. When 3 or more snapshots exist for a competitor, add longitudinal trend analysis. - Update
usage-history.jsonwith the run metadata.
Guardrails
- Never fabricate competitor data. If a fetch fails or a dimension has no data, state the gap.
- Separate raw data (snapshots) from interpretation (reports).
- Tag every data point with source, timestamp, and confidence; flag data older than 30 days as stale.
- Recommend only legal, ethical competitive responses. Collect only publicly available professional information.
Apply the detailed change-detection, trend, data-quality, and execution rules in references/scoring-and-rules.md throughout.
Related Skills
onewave-ai/gmail-to-crm-pipeline
tools
VerifiedTrustedCommunity
Uses MCP Connectors to read Gmail inbound leads, score them by ICP fit, draft personalized responses, and log qualified leads to your CRM. Turns your inbox into an automated pipeline.
172SKILL.mdUpdated Jun 5, 2026
onewave-ai/full-codebase-migrator
development
VerifiedTrustedCommunity
Uses 1M context window to ingest an entire codebase and output a file-by-file migration plan. Supports JS to TS, React class to hooks, framework migrations, and more. Generates migration-plan.md with file inventory, dependency graph, migration order, file-by-file changes, estimated effort, and risk assessment.
172SKILL.mdUpdated Jun 5, 2026
onewave-ai/financial-document-parser
development
VerifiedTrustedCommunity
Extract and analyze data from invoices, receipts, bank statements, and financial documents. Categorize expenses, track recurring charges, and generate expense reports. Use when user provides financial PDFs or images.
172SKILL.mdUpdated Jun 5, 2026
onewave-ai/expansion-revenue-finder
tools
VerifiedTrustedCommunity
Identifies upsell and cross-sell opportunities within existing customer accounts. Analyzes product usage, feature gaps, team growth, industry benchmarks, and competitive pressure to surface revenue expansion plays scored by potential, effort, and likelihood. Generates an expansion-playbook.md with account-by-account opportunities, recommended pitch, timing, and approach.
172SKILL.mdUpdated Jun 5, 2026