Agent skill

Conversion Optimization

by wondelai in wondelai/skills

Guided journey from a leaking conversion flow - landing page, signup, checkout, or in-app onboarding - to a measured, tested funnel.

MITAuto-check passedMarketing & SEO

Install Conversion Optimization

skills CLI
$ npx skills add wondelai/skills --skill conversion-optimization -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install wondelai/skills conversion-optimization --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/wondelai/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/conversion-optimization .claude/skills/conversion-optimization && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
conversion-optimization
GitHub stars
2.4k
Token cost
~6.6k tokens
SKILL.md length
3,662 words
Files
3 (incl. references)
Skills in repo
62
Repo updated
First seen
Licence
MIT

At a glance

Guided journey from a leaking conversion flow - landing page, signup, checkout, or in-app onboarding - to a measured, tested funnel.

  • Works in 7 steps: Find the leak (lean-analytics) — GATE → Research why they leave… → Fix the message at the leak… → …
  • The user wants to raise conversion on a specific flow
  • SKILL.md covers Core Principle, Journey Map, Operating Rules and Intake, plus 4 more sections
  • Calls npx

What it does

Conversion Optimization is an agent skill from wondelai/skills. Guided journey from a leaking conversion flow - landing page, signup, checkout, or in-app onboarding - to a measured, tested funnel. Orchestrates six skills phase by phase - lean-analytics, cro-methodology, storybrand-messaging, hundred-million-offers, influence-psychology, design-everyday-things - each phase carries its full method inline so it runs standalone, asking the user questions at every decision point and recording results in the project docs/ folder (FUNNEL.md, METRICS.md, EXPERIMENTS.md…

Its SKILL.md is about 6.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/artifact-templates.md` and `references/methods.md`).

It sits in Marketing & SEO, covering Conversion rate optimization. The repository describes itself as: Wondel.ai Agent Skills — Business, Marketing, UX & Coding Frameworks from Bestselling Books. 50 skills + 12 guided journeys for Claude Code, Codex, Cursor & other agentskills.io… The licence is MIT.

When your agent uses it

  • The user wants to raise conversion on a specific flow
  • Signup abandonment
  • Diagnose onboarding drop-off
  • Says people start but never finish

Example prompts

  • “people start but never finish”
  • “/conversion-optimization”

Requirements

  • Node.js

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Find the leak (lean-analytics) — GATE
  2. Research why they leave (cro-methodology) — GATE
  3. Fix the message at the leak (storybrand-messaging)
  4. Make the offer worth acting on (hundred-million-offers)
  5. Put proof at every doubt (influence-psychology)
  6. Remove the friction (design-everyday-things)
  7. Prove it (cro-methodology)

What it can do on your machine

Read from SKILL.md and the folder at commit c172996. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • npx

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npx, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Conversion Optimization loads about 6.6k tokens when it runs, and up to ~12k if it reads all its reference files. Until then it costs about 261 tokens; SKILL.md has 3,662 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~261
When it runs · the whole SKILL.md, loaded when a task matches
~6.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~12k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from wondelai/skills at commit c172996, republished under its MIT licence (© wondelai). 3,662 words, ~6,619 tokens.

Download SKILL.mdSave it as .claude/skills/conversion-optimization/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
conversion-optimization
description
Guided journey from a leaking conversion flow - landing page, signup, checkout, or in-app onboarding - to a measured, tested funnel. Orchestrates six skills phase by phase - lean-analytics, cro-methodology, storybrand-messaging, hundred-million-offers, influence-psychology, design-everyday-things - each phase carries its full method inline so it runs standalone, asking the user questions at every decision point and recording results in the project docs/ folder (FUNNEL.md, METRICS.md, EXPERIMENTS.md, CONVERSION-OPTIMIZATION-PLAN.md) so the journey resumes across sessions. Use when the user wants to raise conversion on a specific flow, fix checkout or signup abandonment, diagnose onboarding drop-off, or says 'people start but never finish'. With no site yet, use create-website; for a whole-site look, message, and speed audit, improve-website; if the flow converts but needs traffic, grow-website; for in-product engagement and retention, improve-app. For one framework in isolation, invoke that skill directly.
license
MIT
metadata.author
wondelai
metadata.version
1.0.0

Conversion Optimization

Turn one leaking conversion flow — a landing page, a signup, a checkout, an in-app onboarding — into a measured, tested funnel. This is an interactive, resumable journey of seven phases: the agent asks before every decision and records the outcome in your project's docs/ folder, so you can stop after any phase and pick up later. It works on websites and inside products alike; the unit of work is the flow and its ONE action, not the whole site.

Core Principle

Find the leak with numbers, learn the reason from customers, fix message → offer → proof → friction in that order, and prove every fix with a pre-committed test. The order is causal: a number tells you where, only research tells you why, motivation must be raised before friction-cutting pays, and an untested fix is a guess that compounds. This skill sequences the phases, asks the decision questions, and records every choice in docs/. The constituent skills carry the method — invoke them rather than improvising their frameworks.

Journey Map

PhaseSkillQuestion it answersArtifact
1lean-analyticsWhere does the flow actually leak, and what is the one metric?Extends docs/METRICS.md — GATE
2cro-methodologyWhy do people drop at the leak — which objections and friction?Creates docs/FUNNEL.md; extends docs/EXPERIMENTS.md — GATE
3storybrand-messagingDoes the leaking step promise the visitor's own desired outcome in five seconds?Extends docs/POSITIONING.md + docs/FUNNEL.md + docs/EXPERIMENTS.md
4hundred-million-offersIs the offer at the conversion point worth acting on now?Extends docs/OFFER.md + docs/EXPERIMENTS.md
5influence-psychologyIs there honest proof at every point of doubt?Extends docs/FUNNEL.md + docs/EXPERIMENTS.md
6design-everyday-thingsCan a visitor who decided to act complete the flow without stumbling?Extends docs/FUNNEL.md + docs/DESIGN.md + docs/EXPERIMENTS.md
7cro-methodologyWill we know the fix worked — pre-committed metric, sample size, no peeking?Extends docs/EXPERIMENTS.md + docs/METRICS.md

Operating Rules

  1. Resume first. Before anything else, read docs/CONVERSION-OPTIMIZATION-PLAN.md and every artifact in the Journey Map. If the tracker exists, summarize the journey state in 3-5 lines and ask which phase to enter. Done when the user has confirmed an entry point. A journey with a tracker is resumed, never restarted.
  2. Intake on first run only. No tracker: run the Intake below, then create docs/CONVERSION-OPTIMIZATION-PLAN.md with every phase statused pending | in-progress | awaiting-evidence | done | deferred: reason | skipped: reason. Done when the tracker exists and the user has confirmed the phase plan.
  3. Phase entry. Announce: what the phase does, the decision it forces, the artifact it produces, rough effort. Offer proceed / skip / defer — phases marked GATE may be deferred, never skipped. Mark the phase in-progress on proceed. Done when the user chose.
  4. Skill invocation and fallback. Load the phase's skill and use it: each phase's Invoke line names the skill by slug — use that skill to run the phase. If it is not available, offer: npx skills add wondelai/skills/<slug> --global. If the user declines, run the phase from its Brief — the minimum viable method. State which mode you are in.
  5. In-phase decisions. Ask every question under "Decide with the user" — with concrete options and your recommendation. Record the choice in the tracker's Key Decisions. A decision made silently is a defect.
  6. Phase exit. Present the draft artifact content for sign-off before writing. On approval: write or extend the docs/ files, update the tracker (status, Key Decisions, Next Actions). Done when the files are written and the phase row shows done.
  7. Artifact discipline. Read before writing; create a file only if missing, otherwise extend — add or update your sections, preserve everyone else's. Files are UPPERCASE in docs/. Every recommendation lands as a checkbox or a table row with owner and priority. See references/artifact-templates.md when creating a docs/ file for the first time — create it from the full skeleton (all section headings), then fill the sections your phase names.
  8. Measure, research, then change — and every change is a test. No fix ships without a Phase 1 leak and a Phase 2 researched reason behind it, and every shipped change lands in docs/EXPERIMENTS.md with a pre-committed primary metric and a guardrail. A fix with no research behind it goes back to Phase 2; a bold change with no test attached stays in the backlog until it has one.

Intake

Ask these before creating the tracker:

  1. Which flow are we optimizing, and what is the ONE action at its end? (Scopes every phase — a flow with three competing CTAs has no goal.)
  2. Where do the numbers say people drop — analytics, funnel steps, cohort data? Paste what you have. (Feeds the Phase 1 leak diagnosis; no instrumentation means Phase 1 starts by adding it.)
  3. Roughly how much traffic or volume enters the flow per week? (Gates Phase 7 — decides whether A/B tests can reach significance or the journey leans on qualitative evidence and before/after windows.)
  4. What voice-of-customer sources exist or can be gotten — exit surveys, session recordings, support tickets, sales calls, reviews — and can you paste or export the raw text of the best one? (Phase 2 objections must quote the customer's own words, so the phase needs the content, not just the source name.)
  5. What is the current offer at the conversion point — price, guarantee, bonuses — and can it change? (Gates Phase 4; a contractually fixed offer narrows it to presentation.)
  6. Do docs/POSITIONING.md or docs/OFFER.md already exist from another journey? (Phases 3-4 build on them rather than restarting.)
  7. How much of the journey do you want now? (Phases 1-2 are the mandatory diagnosis; 3-6 are the fix passes aimed by it; 7 turns fixes into proof.)

Skip heuristics: skip Phase 3 when messaging was already validated (e.g. an improve-website journey completed its message phases); skip Phase 4 when the offer is fixed by contract — record skipped: reason. Phase 7 may be deferred: reason at very low traffic in favor of before/after evidence with an explicit revert trigger, never silently skipped. Never skip Phases 1-2 — an unfound leak and an unresearched reason turn every later phase into guessing.

Then create docs/CONVERSION-OPTIMIZATION-PLAN.md from the template and confirm the plan. Done when the tracker exists with every phase statused and the user has confirmed the plan.

Phases

Phases run in the listed order — each assumes the previous phase's artifact exists. Any phase can be entered, skipped, or deferred per the Operating Rules, but Phases 1-2 gate them all: nothing downstream fixes a problem that isn't a measured leak with a researched reason. When running any phase from its Brief (constituent skill not installed), read references/methods.md first — it carries each phase's full method, checklists, formulas, and benchmarks; the Brief is only the summary.

Phase 1 — Find the leak (lean-analytics) — GATE

Purpose: Locate where the flow actually loses people and pick the one metric this journey moves — before any opinion about why.

Brief (fallback): A good metric is a comparative ratio that changes what you do next; totals and cumulative charts are vanity. Express each step of the flow as a conversion rate, compare against your own history and published benchmarks (e-commerce converts ~1-3% of visitors; landing pages on paid traffic low single digits), and find the biggest absolute drop on the highest-value path. Pick the One Metric That Matters for this journey, pair it with a counter-metric so it can't be gamed (signup rate × 30-day retention), and draw a line in the sand: target, date, pre-committed miss response. Cohort and segment (channel, device, plan) — one collapsing segment hides inside a flat average.

Invoke: Use the lean-analytics skill with the flow steps and analytics from intake. Ask for a step-by-step funnel table with baselines and benchmarks, the OMTM plus counter-metric for this journey, and the biggest leak ranked by absolute lost value.

Decide with the user: (1) Confirm the OMTM and its counter-metric. (2) Which leak to attack first — biggest absolute loss on the money path, not the easiest percentage. (3) If instrumentation is missing, which minimal events to add first — the phase stays awaiting-evidence until the numbers exist.

Artifact: Extend docs/METRICS.md ## Funnel (stage | conversion | benchmark | bottleneck?), ## Stage & One Metric That Matters, and ## Baselines & Targets. Update the tracker.

Done when: the funnel is measured at the coarsest granularity that still localizes the leak to a single step, the OMTM and counter-metric are recorded with a line in the sand, and the leak is named — only then are Phases 2-7 unlocked. Finer sub-steps awaiting instrumentation stay awaiting-evidence in Next Actions and do not block the journey, provided the named leak does not depend on them.

Phase 2 — Research why they leave (cro-methodology) — GATE

Purpose: Replace guesses about the leak with evidence from real visitors. Phases 3-6 may only fix problems traceable to a finding here.

Brief (fallback): Don't guess — discover. Mine primary sources (a one-question exit survey: "What's preventing you from [action] today?"; post-conversion: "What almost stopped you?"; chat logs, tickets, sales calls) and secondary sources (reviews, competitors) for the customer's own words. Sort objections into the Big 5 — Trust, Price, Fit, Timing, Effort — and build the O/CO table: every objection gets an evidence-backed counter placed at the exact step the doubt arises, never in an FAQ. Diagnose each step with the LIFT lenses (value proposition ± clarity, relevance, urgency, minus anxiety and distraction — Goward) and the MECLABS heuristic (conversion rises with motivation and value clarity, falls with friction and anxiety). Rank fix hypotheses by ICE and apply the 10x screen: if a change couldn't plausibly double the step, don't queue it.

Invoke: Use the cro-methodology skill with the Phase 1 leak, the flow, and the voice-of-customer sources from intake. Ask for the researched objection list in customer words, the O/CO table with placements, missing persuasion assets, and an ICE-ranked hypothesis backlog.

Decide with the user: (1) Which researched objection is the primary leak driver. (2) Low traffic: accept qualitative plus heuristic evidence — explicitly. (3) Which implicit objections need CO-Only counters (countered without being stated).

Artifact: Create docs/FUNNEL.md with ## Flow Map & ONE Action, ## Leak Diagnosis, and ## Objections & Counters (O/CO); extend docs/EXPERIMENTS.md ## Experiment Backlog (ICE-ranked). METRICS.md ## Funnel stays canonical for the conversion numbers — Leak Diagnosis cites them and adds the researched reason and severity. Update the tracker.

Done when: the flow map names the ONE action per step, every researched objection has an evidence-backed counter and a placement, and the backlog is ICE-ranked.

Phase 3 — Fix the message at the leak (storybrand-messaging)

Purpose: Make the leaking step say what the visitor gets, in their words, in five seconds — clarity converts before persuasion can.

Brief (fallback): The customer is the hero; you are the guide. Run SB7 on the leaking step: a Character who wants one thing, their Problem at three levels (external, internal — the frustration the copy must name, philosophical), you as the Guide (empathy + authority), a 3-step Plan that makes acting feel safe, one Direct plus one Transitional CTA, and named failure/success stakes. Rewrite the step's headline in customer language pulled straight from Phase 2 — customer words outperform copywriter words. Then make it stick (Made to Stick): concrete beats abstract ("save 16 hours a month," not "boost productivity"), and pick the single Commander's Intent message the visitor must still remember tomorrow.

Invoke: Use the storybrand-messaging skill with the step's current copy, the Phase 2 objection evidence, and POSITIONING.md if it exists. Ask for above-the-fold rewrites that name the internal problem, a one-liner, and one Direct plus one Transitional CTA.

Decide with the user: Which rewrite passes the 5-second test (a stranger can say what's offered and why it matters); which internal problem the copy names; whether the step keeps a transitional CTA or goes single-CTA.

Artifact: Extend docs/POSITIONING.md ## Brand Script (StoryBrand), ## One-Liner, and ## Key Messages (surface | message | status); record the rewrite in the Proposed message/CTA column of docs/FUNNEL.md ## Flow Map & ONE Action, leaving Current message/CTA intact as the before-state Phase 7 measures against; append copy tests to docs/EXPERIMENTS.md ## Experiment Backlog. Update the tracker.

Done when: the leaking step has a rewritten message that names the internal problem, one primary CTA, and a logged test hypothesis.

Phase 4 — Make the offer worth acting on (hundred-million-offers)

Purpose: Strengthen what is actually exchanged at the conversion point — the best flow cannot sell a weak offer, and the offer is the biggest single lever.

Brief (fallback): Value = (Dream Outcome × Perceived Likelihood) ÷ (Time Delay × Effort & Sacrifice). Raise the numerator with outcome language and proof; crush the denominator with speed ("first result in 5 minutes") and done-for-you framing. Reverse the risk with a guarantee aimed at the top Phase 2 objection — it raises perceived likelihood and lowers anxiety at once. Stack named, honestly-valued bonuses that each kill one objection; present price after value, anchored against the stack. Scarcity and urgency only when real — fake deadlines convert once and churn forever.

Invoke: Use the hundred-million-offers skill with the current offer from intake and the Phase 2 Price/Timing/Effort objections. Ask for a Value Equation score per lever, a guarantee design matched to the top objection, and a trim-and-stack pass on the offer components.

Decide with the user: Which guarantee the business can actually honor; which bonuses are real and sustainable; whether price presentation changes (anchoring, payment plans) — pricing itself may be out of scope; record that.

Artifact: Extend docs/OFFER.md ## Offer Stack (element | description | honest value | objection it kills), ## Price Metric when the flow raises what the price is charged per, plus ## Willingness-to-Pay Evidence if new evidence surfaced; append offer tests to docs/EXPERIMENTS.md ## Experiment Backlog. Update the tracker.

Done when: each Value Equation lever has a concrete change or a reason it stays, the guarantee targets the top researched objection, and every offer change carries a test hypothesis.

Show full SKILL.md (1,418 more words)Show less
Phase 5 — Put proof at every doubt (influence-psychology)

Purpose: Answer each remaining objection with honest evidence placed at the exact step the doubt arises.

Brief (fallback): Under uncertainty people use shortcuts: social proof (specific numbers — "2,347 teams" — and similar-others beat generic praise), authority (credentials, certifications), commitment (a small first yes makes the big yes consistent — ask for the card after the value moment, not before), reciprocity (give the useful thing first), and scarcity (real only). Audit the flow for proof gaps: every O/CO row needs its counter actually rendered — testimonial, data point, logo bar, guarantee seal — at its placement. Proof hierarchy: specific results with context > named testimonials with faces > case studies > statistics > logos. The transparency test gates everything: if knowing the technique would make the visitor feel tricked, it fails. Fabricated proof and hidden costs are defects, not tactics.

Invoke: Use the influence-psychology skill with the FUNNEL.md O/CO table and the flow's current proof. Ask for a per-step proof audit, which principle answers each open objection, and copy for the two highest-impact placements.

Decide with the user: Which proof assets exist versus must be acquired (testimonial requests, case studies — log acquisition as Next Actions); where scarcity or urgency claims are genuinely true; which steps get a commitment micro-ask.

Artifact: Extend docs/FUNNEL.md ## Proof Inventory (asset | type | placement | status) and complete the ## Objections & Counters (O/CO) placements; append proof tests to docs/EXPERIMENTS.md ## Experiment Backlog. Update the tracker.

Done when: every open objection row has a real proof asset placed or an acquisition task with an owner, and no claim in the flow is unverifiable.

Phase 6 — Remove the friction (design-everyday-things)

Purpose: Protect the visitors who decided to act. B=MAP: behavior happens when Motivation, Ability, and a Prompt converge — Phases 3-5 raised motivation; this phase raises ability and sharpens prompts.

Brief (fallback): Bridge Norman's two gulfs. Execution: clear signifiers (buttons look pressable, fields look editable) and constraints that make errors impossible (date picker over free text, submit disabled until valid). Evaluation: feedback within 0.1s of every action, progress indication on multi-step flows. Forms (Baymard): every field costs conversions — cut to the minimum, ask for payment as late as possible, show all costs before the final step (surprise shipping and taxes is the #1 checkout killer), offer guest checkout, validate inline with messages that say how to fix. Error messages state what went wrong and how to fix it, without blame; slips get undo, not are-you-sure dialogs.

Invoke: Use the design-everyday-things skill with the conversion-critical steps (form, payment, confirmation). Ask for weak signifiers, where constraints replace error messages, feedback gaps, field-by-field form cuts, and message rewrites.

Decide with the user: Which fields are truly required now versus collectable later; where a constraint replaces a warning; whether the flow shows total cost earlier; which severity-4 friction items ship immediately as a logged before/after card versus wait for a full test.

Artifact: Extend docs/FUNNEL.md ## Flow Friction Audit (step | issue | severity 0-4 | fix | status); extend docs/DESIGN.md ## UX Audit Findings for reusable component fixes, naming the Norman gulf (execution or evaluation) in the Heuristic column; append fixes to docs/EXPERIMENTS.md ## Experiment Backlog. Update the tracker.

Done when: every step has a friction audit row, forms are cut to minimum fields, severity-4 items have owners, and error messages meet the checklist. Where money changes hands in this flow, all costs are visible before the final step and guest checkout is offered; in a flow that takes no payment, mark those two rows n/a.

Phase 7 — Prove it (cro-methodology)

Purpose: Turn the high-ICE fixes into trustworthy experiments — without rigor you cannot tell a real lift from noise, and a false winner compounds forever.

Brief (fallback): Pre-commit everything (Kohavi): primary metric, guardrail metrics (the Phase 1 counter-metric, revenue per visitor, support volume), sample size computed from baseline rate and minimum detectable effect at 95% significance / 80% power, and a duration of at least one full business cycle covering weekdays and weekends. Never peek and stop early — it manufactures false positives; never rerun until you like the answer. Test bold changes — meek tweaks rarely reach significance. Low traffic: run a before/after window with qualitative confirmation, or ship as a reversible bet with an explicit revert trigger — and say which you are doing. Practical significance gates rollout: a statistically significant 0.1% lift may not pay for its complexity. Winners become the new control; losers become learnings written down.

Invoke: Use the cro-methodology skill with the top ICE hypotheses from the backlog. Ask for full experiment designs: hypothesis in "If [change], then [metric] because [research]" form, pre-committed sample size and duration, and the decision rule.

Decide with the user: Which 1-3 hypotheses run first (highest ICE on the money path); the guardrail metrics; what happens on a flat result — iterate the fix, or return to Phase 2 for better research.

Artifact: Promote backlog rows to docs/EXPERIMENTS.md ## Experiment Cards, adding the pre-committed sample size per arm, planned duration, and the minimum lift worth keeping as extra bullets on the card (the skeleton's bullets carry hypothesis, metrics, and decision rule; extra bullets are additive and allowed); record results and verdicts as they land; extend docs/METRICS.md ## Baselines & Targets with a new dated row per tested metric, leaving the pre-test baseline row intact. Update the tracker.

Done when: each shipped fix is a card with a pre-committed metric, sample size, and decision rule; results carry verdicts; and the OMTM's new baseline is written down.

Optional Phases

SkillAdd whenArtifact
ux-heuristicsthe whole page confuses, not just the flow — visitors stumble before reaching the conversion stepsExtends docs/DESIGN.md ## UX Audit Findings
microinteractionsthe flow's moments feel dead — silent taps, unexplained waits, abrupt state changesExtends docs/DESIGN.md ## Microinteraction Inventory
scorecard-marketingthe flow needs a lower-commitment entry — a quiz or assessment as the transitional conversionExtends docs/WEBSITE.md ## Lead Capture
hooked-uxthe conversion sticks but the next visit doesn't — post-conversion activation is the real leakExtends docs/PRODUCT.md ## Hook Model

Optional phases follow the same operating rules — load and use each listed skill exactly as a core phase would; insert where the Add-when condition first becomes true. They carry no inline Brief: standalone, run ux-heuristics as a severity-rated pass over Nielsen's 10 heuristics, microinteractions as a trigger/rules/feedback/loops inventory, scorecard-marketing as a quiz-funnel design ending in a personalized result, and hooked-ux as a trigger → action → variable reward → investment loop audit — or install the named skill for its full framework.

Common Mistakes

MistakeFix
Redesigning the step before measuring where the leak isRun Phase 1 first — the biggest drop is rarely where opinion points; optimize the money path, not the loudest complaint.
Guessing objections instead of mining customer wordsExit surveys, tickets, and sales calls (cro-methodology) — teams are almost always wrong about why visitors leave.
Polishing persuasion on top of an unclear messageClarity before psychology: pass the 5-second test (storybrand-messaging) before adding proof and urgency.
Treating the offer as fixed and testing only cosmeticsThe offer is the biggest lever (hundred-million-offers); a guarantee change outlifts a button change by orders of magnitude.
Faking scarcity or cherry-picking proofConverts once, churns forever, caps trust permanently — real scarcity and verifiable proof only (influence-psychology).
Adding form fields "while we're at it"Every field costs conversions (Baymard); collect later what you don't need now (design-everyday-things).
Peeking at test results and stopping earlyPre-commit sample size and duration, then report whatever comes back (cro-methodology, Kohavi).

Completing the Journey

A funnel always has a next-biggest leak: when the Phase 7 verdicts land, re-enter Phase 1 with fresh numbers rather than declaring victory — the journey is a loop with an exit condition, and the exit condition is the line in the sand from Phase 1, not exhaustion.

Exit checklist — every box tied to an artifact:

  • Every phase in docs/CONVERSION-OPTIMIZATION-PLAN.md is done, deferred: reason, or skipped: reason.
  • The OMTM, counter-metric, and line in the sand are recorded with pre- and post-test baselines (METRICS.md).
  • Every researched objection has a placed, verifiable counter (FUNNEL.md O/CO and Proof Inventory — no open rows on the money path).
  • The flow's forms and steps carry no severity-4 friction without an owner (FUNNEL.md Flow Friction Audit).
  • Each shipped change is an Experiment Card with a pre-committed metric and a recorded verdict (EXPERIMENTS.md).

Close the tracker: remaining Next Actions carried into FUNNEL.md and EXPERIMENTS.md so nothing is lost. Then route forward: when the flow converts and needs more qualified traffic, continue with the grow-website skill; when the leak has moved past conversion into engagement and retention, continue with the improve-app skill; when the whole site — look, typography, speed, message — needs the broader pass, continue with the improve-website skill.

© wondelai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in conversion-optimization of wondelai/skills.

  • SKILL.md
  • references/artifact-templates.md
  • references/methods.md

Open the folder on GitHubat commit c172996

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Categories

Questions about Conversion Optimization

What does Conversion Optimization do?

Guided journey from a leaking conversion flow - landing page, signup, checkout, or in-app onboarding - to a measured, tested funnel. Conversion Optimization is an agent skill from wondelai/skills. Guided journey from a leaking conversion flow - landing page, signup, checkout, or in-app onboarding - to a measured, tested funnel.

When should I use Conversion Optimization?

Conversion Optimization fits situations like: the user wants to raise conversion on a specific flow; signup abandonment; diagnose onboarding drop-off; says people start but never finish.

How do I install Conversion Optimization in Claude Code?

Run `npx skills add wondelai/skills --skill conversion-optimization -a claude-code`. Or copy the skill folder (conversion-optimization in wondelai/skills) into .claude/skills/conversion-optimization in your project. Claude Code loads it when a task matches its description.

How do I install Conversion Optimization in Codex?

Run `npx skills add wondelai/skills --skill conversion-optimization -a codex`. Or copy the skill folder (conversion-optimization in wondelai/skills) into .agents/skills/conversion-optimization in your project. Codex loads it when a task matches its description.

Can I use Conversion Optimization in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add wondelai/skills --skill conversion-optimization -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/conversion-optimization, .gemini/skills/conversion-optimization, .github/skills/conversion-optimization and .opencode/skills/conversion-optimization in your project.

What does Conversion Optimization need to run?

Going by SKILL.md and its folder, Conversion Optimization needs the command-line tools its instructions call (npx). Our summary lists: Node.js.

Does Conversion Optimization access the network?

SKILL.md contains no URLs. Its commands use npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Conversion Optimization safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Conversion Optimization use?

Conversion Optimization is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Conversion Optimization use?

About 6.6k tokens (SKILL.md is roughly 26k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5.6k tokens, read only when the agent opens those files.

What are the alternatives to Conversion Optimization?

Skills that share tags, products or a category with Conversion Optimization: FLOW SEO Framework (AgriciDaniel/claude-seo, 18k stars), Onboarding Cro (freekmurze/dotfiles, 1k stars), Google Analytics (thatrebeccarae/claude-marketing, 162 stars) and Paywall Upgrade Cro (freekmurze/dotfiles, 1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Conversion Optimization?

wondelai (a GitHub organization) maintains it in wondelai/skills, which has 2,350 GitHub stars. The repository holds 62 skills in this directory. The repository was last updated on September 10, 2026.

Source: wondelai/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.