Slash Command

/okr-plg-signals

Analyze PLG and hybrid-motion signals to produce benchmark-aware OKR guidance for product-sourced growth

Install

Run in your terminal

npx claudepluginhub revpalsfdc/opspal-commercial --plugin opspal-okrs

Details

Argument--org <org-slug> [--cycle <Q3-2026|H2-2026>] [--audience exec|product|revenue] [--format markdown|json]

Command Content

Stats

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Last CommitMar 18, 2026

Actions

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# 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

What This Does

Pulls product funnel evidence from product analytics and supporting CRM context

Benchmarks core PLG metrics such as visitor-to-signup, activation, and paid conversion

Separates motion ownership across self-serve, sales-assisted, and sales-led paths

Recommends KRs that connect product behavior to revenue outcomes

Flags handoff rules so hybrid motion attribution is explicit

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

Execution

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-plg-signals Command

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.

Usage

# 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

What This Does

Pulls product funnel evidence from product analytics and supporting CRM context
Benchmarks core PLG metrics such as visitor-to-signup, activation, and paid conversion
Separates motion ownership across self-serve, sales-assisted, and sales-led paths
Recommends KRs that connect product behavior to revenue outcomes
Flags handoff rules so hybrid motion attribution is explicit

Output

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

Execution

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`
});

Related Commands

/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