3.0.0-beta.15). Features may change before the next stable release.Switch to stable →Skills
Audit a non-signup form with ak:form-cro
Review form friction, data necessity, accessibility, measurement, and test hypotheses before approving implementation.
Use ak:form-cro to audit a lead-capture, contact, demo-request,
application, survey, checkout, or quote-request form. It aims for more qualified
completions, not just more submissions, while preserving fields the business,
security, or law needs. Its output includes prioritized findings, a proposed
field design, copy and error guidance, and test hypotheses—not live form changes.
Choose ak:form-cro for a non-signup form
Use ak:form-cro when
- You need to understand form starts, completion, field errors, abandonment, or mobile differences.
- You want to justify every required and optional field against the follow-up process and compliance needs.
- You need recommendations for layout, labels, validation, multi-step flow, submit states, or post-submit expectations.
Choose another workflow when
- The form creates an account. Use the signup-flow CRO workflow.
- The form sits inside a popup and the container behavior is the main issue. Use the popup CRO workflow.
- The surrounding page, offer, or traffic quality is the primary problem. Audit that broader surface before attributing the result to the form.
- You already selected a testable change. Use
ak:ab-test-setupto design the experiment.
Prepare the form evidence
Provide the form URL, screenshots, or field list; the form type and audience; what happens after submission; current starts and completions; field-level errors and drop-off; device split; and the fields actually used downstream. Also provide accessibility, consent, privacy, retention, security, and legal requirements. Remove secrets and unnecessary personal records.
Complete Onboarding, and confirm Marketing Kit is installed for the runtime and scope you are using.
| Runtime | Invocation | Availability boundary |
|---|---|---|
| Claude Code | /ak:form-cro ... | Native delivery is the default; explicit plugin delivery is also supported. |
| Cursor | /ak:form-cro ... | Slash invocation is user-verified; broader runtime parity is not implied. |
| Codex | $ak:form-cro ... | The Skill uses native Codex discovery; Hook projection is partial. |
See Runtime adapters for component-level differences.
Run the Skill
/ak:form-cro "Audit this demo-request form using the supplied field analytics. Minimize personal data, preserve required consent and accessibility, propose tests, and do not edit or publish the form"/ak:form-cro "Audit this demo-request form using the supplied field analytics. Minimize personal data, preserve required consent and accessibility, propose tests, and do not edit or publish the form"$ak:form-cro "Audit this demo-request form using the supplied field analytics. Minimize personal data, preserve required consent and accessibility, propose tests, and do not edit or publish the form"Understand the review stages
- Classify the form. The Skill identifies the form's purpose, audience, qualified completion outcome, follow-up process, and business constraints.
- Establish evidence. It reviews starts, submissions, field drop-off, validation errors, completion time, and device differences without inventing missing baselines. Missing analytics is a finding: instrument the flow first rather than guessing which changes will work.
- Audit fields and flow. It challenges field necessity, required status, order, grouping, conditional logic, multi-step behavior, and progress saving. Every proposed removal or deferral names the downstream owner and use, or marks that information as unknown and requiring confirmation before shipping.
- Review interaction quality. It covers persistent labels, useful help, keyboard and autofill behavior, accessible errors, preserved input, loading, success, and failure states.
- Prioritize recommendations. Each change cites evidence or is labeled a hypothesis, with a priority and a metric that would validate its effect. Expected conversion effects are not promises.
- Define measurement. Judge success on qualified completions: valid, usable submissions divided by eligible form starts, with qualification and the observation window defined. View, start, field, error, submit, and success events support diagnosis and bounded experiments.
Field, layout, multi-step, error, button, trust, mobile, and measurement guidance remains available as needed. The Skill consults at most one relevant reference per task; it does not require every checklist for every audit.
Keep consent and implementation separate
Less friction must not mean less informed choice
Do not remove required disclosures, preselect consent, hide optional status, misrepresent urgency, or make refusal harder than submission. Conversion does not override privacy, accessibility, security, or legal obligations.
- Ask only for data that has a documented purpose, lawful basis where required, retention rule, and owner.
- Do not infer or enrich sensitive attributes without approval and a valid data policy. A provider name in a recommendation does not authorize network access or data transfer.
- Keep labels visible, errors specific, input preserved, and keyboard-only and assistive-technology paths usable.
- Treat phone numbers, free-text messages, payment details, and application data according to their sensitivity, not as ordinary conversion fields.
- Do not invent privacy or security assurances, response times, testimonials, badges, or other social proof. Confirm claims against the actual policy, data flow, and supplied evidence before using them.
- Approve code edits, analytics changes, vendor configuration, publishing, and production rollout separately from the audit.
Review the outputs and evidence
A complete result should include:
- A form audit with evidence or a labeled hypothesis, impact rationale, recommendation, priority, and validation metric for every change.
- A justified required/optional field list, order, conditional behavior, labels, help text, error copy, submit copy, and post-submit states. Each removal or deferral names its downstream owner and use or flags confirmation as pending.
- Mobile and accessibility considerations.
- An event plan that avoids capturing field values unless explicitly required.
- Test hypotheses with qualified completions as the primary outcome, supporting metrics, guardrails, and assumptions.
- A clear boundary between recommendations and any separately approved implementation work.
Troubleshoot the workflow
| Symptom | Safe next step |
|---|---|
| No field-level evidence exists | Add privacy-reviewed start, error, submit-attempt, and success events before ranking fields by impact. |
| More leads arrive but quality falls | Judge success on qualified completions, not raw submissions, and review whether necessary downstream context was removed. |
| A field is legally required | Keep it, explain why it is needed, and test clarity or timing rather than silently deleting it. |
| Mobile abandonment is high | Verify keyboard type, autofill, tap targets, viewport, validation, and data preservation on real devices. |
| The runtime cannot find the Skill | Confirm target and scope, restart the runtime, then follow Runtime cannot find a Skill or Agent. |
Know the limits
- Field-count and layout rules are hypotheses, not universal effect sizes.
- Completion rate alone does not measure lead quality, user understanding, successful payment, or downstream value.
- The Skill cannot verify live accessibility, analytics, compliance, or vendor behavior without the corresponding access and evidence.
Continue with ak:ab-test-setup after choosing a recommendation, or review the
Marketing Kit overview.
Build referral programs with ak:referral-program-building
Design referral rewards, platform requirements, tracking, fraud controls, messages, and measurement while keeping product, data, payout, and send changes reviewable.
Improve post-signup activation with ak:onboarding-cro
Audit first-run friction and design an evidence-led onboarding flow, copy, measurement plan, and bounded experiments.