Analyze PLG and hybrid-motion signals to produce benchmark-aware OKR guidance for product-sourced growth
From opspal-okrsnpx claudepluginhub revpalsfdc/opspal-commercial --plugin opspal-okrs--org <org-slug> [--cycle <Q3-2026|H2-2026>] [--audience exec|product|revenue] [--format markdown|json]Analyze PLG and hybrid-motion performance for OKR planning. This command translates product usage, PQL, and monetization signals into benchmark-aware KRs and handoff guidance.
# Review PLG signals for the current org
/okr-plg-signals --org acme-corp
# Generate a leadership-oriented hybrid-motion readout
/okr-plg-signals --org acme-corp --cycle Q4-2026 --audience exec
# Get machine-readable output for planning workflows
/okr-plg-signals --org acme-corp --format json
| Artifact | Location | Purpose |
|---|---|---|
| PLG signals report | orgs/{org}/platforms/okr/reports/okr-plg-signals-{date}.md | Human-readable PLG and hybrid-motion analysis |
| PLG signals data | orgs/{org}/platforms/okr/reports/okr-plg-signals-{date}.json | Benchmark context, attribution split, and recommended KRs |
This command invokes the okr-plg-specialist agent.
Task({
subagent_type: 'opspal-okrs:okr-plg-specialist',
prompt: `Analyze PLG OKR signals for org: ${org || process.env.ORG_SLUG}
Cycle: ${cycle || 'current or next planning cycle'}
Audience: ${audience || 'exec'}
Format: ${format || 'markdown'}
Produce:
1. Visitor->signup, activation, PQL, and paid conversion benchmark review
2. Product-sourced vs sales-assisted vs sales-sourced attribution split
3. Hybrid handoff trigger guidance
4. Recommended PLG and hybrid-motion KRs`
});
/okr-generate - Build a draft OKR set using the resulting PLG guidance/okr-benchmark - Compare current metrics and targets against peer benchmarks/okr-history - Review whether PLG targets have historically landed