champion-tracker — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited champion-tracker (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Detect when product champions change jobs and qualify their new companies against ICP.
Build the initial champion list from public sources. This is done by the agent, not the script.
review-site-scraper skill to pull G2/Trustpilot reviews. Extract reviewer names + companies.linkedin-post-research skill (Apify-based) to find people who posted about the product./v1/kitchen-sink/person (name + company → profile URL) or ContactOut via Orthogonal.champions.csv with required columns.Use champion_tracker.py for ongoing tracking.
APIFY_API_TOKEN in .env (for LinkedIn profile enrichment)name, linkedin_url (required); original_company, original_title, email, source, notes (optional)Initialize baseline (first run):
# Dry run — see cost estimate
python3 skills/champion-tracker/scripts/champion_tracker.py init -i champions.csv --dry-run
# Create baseline
python3 skills/champion-tracker/scripts/champion_tracker.py init -i champions.csvCheck for job changes (subsequent runs):
# Dry run
python3 skills/champion-tracker/scripts/champion_tracker.py check --dry-run
# Detect changes and output CSV
python3 skills/champion-tracker/scripts/champion_tracker.py check -o changes.csvView status:
python3 skills/champion-tracker/scripts/champion_tracker.py status| Column | Description |
|---|---|
| champion_name | Full name |
| linkedin_url | LinkedIn profile URL |
| previous_company | Company at baseline |
| previous_title | Title at baseline |
| new_company | Current company (changed) |
| new_title | Current title |
| change_detected_date | Date this check was run |
| position_start_date | When they started the new role |
| days_since_change | Days since new position started |
| icp_score | 0-4 ICP qualification score |
| icp_verdict | Strong Fit / Good Fit / Possible Fit / Weak Fit |
| icp_notes | Scoring breakdown |
| Email if available | |
| notes | Original notes from champion CSV |
| Signal | Points | What it checks |
|---|---|---|
| B2B signal | 1.0 | Title contains sales/SDR/revenue/growth keywords |
| Outbound motion | 1.0 | Sales leadership title (VP Sales, Head of Growth, etc.) |
| Company size | 1.0 / 0.5 | SMB/mid-market = 1.0; unknown = 0.5 benefit-of-doubt |
| Seniority | 1.0 | VP, Director, Head of, C-level, Founder |
Verdicts: Strong Fit (>=3) / Good Fit (>=2) / Possible Fit (>=1.5) / Weak Fit (<1.5)
--dry-run always shows cost before any API callsskills/champion-tracker/
SKILL.md # This file
scripts/
champion_tracker.py # Main CLI script
input/
champions_template.csv # Template for manual additions
snapshots/ # Created at runtime
baseline.json # Latest full snapshot
archive/ # Timestamped copies
output/ # Created at runtime
changes-YYYY-MM-DD.csv # Generated outputLinkedInEnricher from skills/lead-qualification/scripts/enrich_leads.pyrequests (Python package), APIFY_API_TOKEN (env var)~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.