Install
$ agentstack add skill-frontal-so-outbound-skills-job-changes ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
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Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Job Change Signals
Job changes are the #2 buying signal by purchase correlation. New leaders have a mandate for early wins, vendor amnesty period, and budget air cover. Response rate is 3x higher than cold outreach, with peak engagement at days 14-45.
Reference Files
- Read
{SKILL_BASE}/resources/timing/job-change-tracking.mdfor Clay setup and tracking methods - Read
{SKILL_BASE}/resources/buying-signals.mdfor signal ranking and benchmarks
Why Job Changes Work
- 3x higher response rate vs cold outreach
- Peak engagement: days 14-45 after the change (vendor amnesty period)
- New leaders actively build their stack in first 90 days
- Trust already established with former champions
- Champion job change to target account = 75 points (Tier 1 signal)
Clay Setup - Two Methods
Method 1: Monitor Existing Table
- Go to Actions > Monitor for Job Changes
- Specify the LinkedIn URL column
- Save and run - new row created for each detected change
Method 2: Create New Tracking Table
- +Create New > Table > Track Job Changes
- Include "Person LinkedIn URL" for future monitoring
- Include "Company LinkedIn URL" to detect if they already changed
Historical vs Future
- Historical: Include both Person + Company LinkedIn URLs - checks if contact already changed
- Future: Only Person LinkedIn URL - monitors ongoing changes
Timing Framework
| Window | Multiplier | Action | |---|---|---| | Days 0-13 | Too early | Monitor only - they are still settling in | | Days 14-45 | Peak (1.5x) | Immediate outreach - vendor amnesty window | | Days 46-90 | Good (1.0x) | Standard outreach - still building stack | | Days 90+ | Declining (0.7x) | Lower priority - stack likely set |
Outreach Template
Hey congrats on the new role at {{company}}.
As you are taking over {{department}}, curious how you are
currently handling {{relevant_problem}}?
We helped {{similar_company}} with exactly that.
Key Rules
- Do NOT mention you tracked their job change ("I saw you moved to...")
- Reference the role/department naturally, not the signal itself
- Former champions get AE-owned outreach (warm relationship)
- New contacts at target accounts get SDR sequence
- Stack with other signals for compound scoring: job change (75pts) + website visit (50pts) = Hot
Examples
Example 1: "Track when my past customers change jobs" -> Set up Clay historical tracking with Person + Company LinkedIn URLs, filter to ICP companies, trigger AE outreach within 24h
Example 2: "Someone just started as VP Sales at a target account" -> Day 14-45 window = peak timing. Send congratulations + reference relevant problem for their new role. AE owns if former champion, SDR if new contact
Example 3: "Build a job change signal workflow in Clay" -> Create tracking table with Person LinkedIn URLs, add enrichment columns (new company, title, start date), filter ICP match, calculate days-since-change, route to Slack alerts for day 14+ changes
Part of Frontal — free, open GTM skills for your AI agent. Browse the library →
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: Frontal-so
- Source: Frontal-so/outbound-skills
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.