The description names the domain (form optimization) and lists form types (lead capture, contact, demo request, application, survey, checkout), but it doesn't describe concrete actions the skill performs — it only describes when to use it, not what it actually does (e.g., 'reduces form fields', 'adds progressive disclosure', 'optimizes field order').

The 'when' is exceptionally well-defined with explicit triggers and boundary conditions (referencing related skills for signup and popup forms). However, the 'what does this do' is weak — it never states what actions or optimizations the skill actually performs, only when it should be selected.

Excellent coverage of natural trigger terms users would say: 'form optimization,' 'lead form conversions,' 'form friction,' 'form fields,' 'form completion rate,' 'contact form,' plus specific form types like 'lead capture forms,' 'demo request forms,' 'checkout forms.'

Highly distinctive with explicit boundary-setting: it clearly excludes signup/registration forms (directing to signup-flow-cro) and popup forms (directing to popup-cro), making it very unlikely to conflict with related skills.

Extremely verbose at ~350+ lines. Much of the content is general UX/form design knowledge Claude already knows (e.g., what inline validation is, that single column is mobile-friendly, that error messages should be specific). Sections like 'Error Handling,' 'Mobile Optimization,' and 'Visual Design' are standard UX principles that don't need to be spelled out at this length.

Provides concrete guidance like specific field recommendations, button copy examples, and measurement metrics, but lacks executable code or implementation snippets. The advice is specific enough to act on (e.g., '44px minimum height') but is mostly descriptive best practices rather than copy-paste ready implementations or templates.

The 'Initial Assessment' section provides a clear starting sequence, and the 'Output Format' section defines deliverables. However, there's no explicit end-to-end workflow tying assessment → recommendations → testing together with validation checkpoints. The process is implied but not explicitly sequenced with feedback loops.

This is a monolithic wall of text with no references to external files for detailed content. The experiment ideas, field-by-field optimization, and form type-specific guidance could easily be split into separate reference files. Everything is inlined in one massive document, making it hard to navigate and consuming excessive context window.