Lists multiple specific concrete actions: 'choose between PLG and sales-led,' 'design a sales motion,' 'optimize time-to-first-value,' 'build a value-before-purchase experience.' Also specifies coverage areas: 'sales motion selection, value delivery design, and go-to-market motion architecture.'

Clearly answers both 'what' (sales motion selection, value delivery design, GTM motion architecture) and 'when' with explicit trigger guidance ('When the user wants to...' and 'Also use when the user mentions...'). Additionally includes negative boundaries ('Do NOT use for technical implementation, code review, or software architecture').

Excellent coverage of natural trigger terms including both acronyms and full forms: 'PLG,' 'product-led growth,' 'sales-led,' 'sales motion,' 'free trial,' 'freemium,' 'self-serve,' 'demo-first,' 'time-to-first-value,' 'TTFV,' 'agent-led sales.' These are terms users would naturally use when discussing go-to-market strategy.

Occupies a clear niche in go-to-market strategy and sales motion design with highly specific trigger terms. The explicit exclusion of technical implementation, code review, and software architecture further reduces conflict risk with engineering-focused skills.

The skill is comprehensive and mostly efficient, but at ~400+ lines it includes some content that could be trimmed or offloaded to reference files. The benchmarks tables and detailed archetype descriptions are valuable but border on excessive for a SKILL.md overview. Some sections like the agent-led discovery section are quite detailed for what could be a reference file.

Highly actionable with concrete decision frameworks (the 2x2 matrix, scoring system with 7+ PLG signals), specific benchmarks with numbers, clear PQL trigger examples, team composition by ARR stage, and step-by-step migration paths. The examples section shows concrete input/output patterns for common user requests.

Multi-step processes are clearly sequenced throughout: the TTFV optimization steps (MAP→ELIMINATE→PRELOAD→GUIDE→MEASURE), motion migration paths with numbered steps and success targets, hybrid motion structure with clear flow diagram, and stage-specific playbooks. Validation checkpoints are present (e.g., 'Target: 25%+ PQL-to-close rate', 'Only viable with tight ICP', signal thresholds for when to add sales).

The skill references `references/quick-reference.md` and related skills at the end, which is good. However, the main body is quite long and monolithic—sections like detailed benchmarks tables, agent-led discovery details, and industry-specific trial rates could be offloaded to reference files. The content that is inline would benefit from being split into separate reference documents with clear pointers.