FLOW SEO Framework
AgriciDaniel/claude-seo
Brings the FLOW framework's stage-specific SEO prompts into the agent, from keyword discovery through backlinks, on-page work and conversion to local SEO, loaded on demand.
Guided journey from a leaking conversion flow - landing page, signup, checkout, or in-app onboarding - to a measured, tested funnel.
$ npx skills add wondelai/skills --skill conversion-optimization -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install wondelai/skills conversion-optimization --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ 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-srcUse ~/.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/
Install the "conversion-optimization" agent skill from https://github.com/wondelai/skills/tree/main/conversion-optimization into .claude/skills/conversion-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conversion-optimization", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/wondelai/skills/tree/main/conversion-optimizationType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add wondelai/skills --skill conversion-optimization -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install wondelai/skills conversion-optimization --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wondelai/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/conversion-optimization .agents/skills/conversion-optimization && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "conversion-optimization" agent skill from https://github.com/wondelai/skills/tree/main/conversion-optimization into .agents/skills/conversion-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conversion-optimization", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add wondelai/skills --skill conversion-optimization -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install wondelai/skills conversion-optimization --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wondelai/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/conversion-optimization .cursor/skills/conversion-optimization && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "conversion-optimization" agent skill from https://github.com/wondelai/skills/tree/main/conversion-optimization into .cursor/skills/conversion-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conversion-optimization", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/wondelai/skills.git --path conversion-optimization--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add wondelai/skills --skill conversion-optimization -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install wondelai/skills conversion-optimization --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wondelai/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/conversion-optimization .gemini/skills/conversion-optimization && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "conversion-optimization" agent skill from https://github.com/wondelai/skills/tree/main/conversion-optimization into .gemini/skills/conversion-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conversion-optimization", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install wondelai/skills conversion-optimizationInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add wondelai/skills --skill conversion-optimization -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/wondelai/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/conversion-optimization .github/skills/conversion-optimization && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "conversion-optimization" agent skill from https://github.com/wondelai/skills/tree/main/conversion-optimization into .github/skills/conversion-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conversion-optimization", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add wondelai/skills --skill conversion-optimization -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install wondelai/skills conversion-optimization --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wondelai/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/conversion-optimization .opencode/skills/conversion-optimization && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "conversion-optimization" agent skill from https://github.com/wondelai/skills/tree/main/conversion-optimization into .opencode/skills/conversion-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conversion-optimization", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
conversion-optimizationGuided 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. 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.
7 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit c172996. It shows what the files ask for, not the result of running them.
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.
Shell commands in SKILL.md call:
npxFrom the folder's file list and the shell code blocks in SKILL.md.
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.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
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.
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.
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.
The full file from wondelai/skills at commit c172996, republished under its MIT licence (© wondelai). 3,662 words, ~6,619 tokens.
.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.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.
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.
| Phase | Skill | Question it answers | Artifact |
|---|---|---|---|
| 1 | lean-analytics | Where does the flow actually leak, and what is the one metric? | Extends docs/METRICS.md — GATE |
| 2 | cro-methodology | Why do people drop at the leak — which objections and friction? | Creates docs/FUNNEL.md; extends docs/EXPERIMENTS.md — GATE |
| 3 | storybrand-messaging | Does the leaking step promise the visitor's own desired outcome in five seconds? | Extends docs/POSITIONING.md + docs/FUNNEL.md + docs/EXPERIMENTS.md |
| 4 | hundred-million-offers | Is the offer at the conversion point worth acting on now? | Extends docs/OFFER.md + docs/EXPERIMENTS.md |
| 5 | influence-psychology | Is there honest proof at every point of doubt? | Extends docs/FUNNEL.md + docs/EXPERIMENTS.md |
| 6 | design-everyday-things | Can a visitor who decided to act complete the flow without stumbling? | Extends docs/FUNNEL.md + docs/DESIGN.md + docs/EXPERIMENTS.md |
| 7 | cro-methodology | Will we know the fix worked — pre-committed metric, sample size, no peeking? | Extends docs/EXPERIMENTS.md + docs/METRICS.md |
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.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.in-progress on proceed. Done when the user chose.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.done.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.Ask these before creating the tracker:
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 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.
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.
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.
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.
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.
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.
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.
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.
| Skill | Add when | Artifact |
|---|---|---|
| ux-heuristics | the whole page confuses, not just the flow — visitors stumble before reaching the conversion steps | Extends docs/DESIGN.md ## UX Audit Findings |
| microinteractions | the flow's moments feel dead — silent taps, unexplained waits, abrupt state changes | Extends docs/DESIGN.md ## Microinteraction Inventory |
| scorecard-marketing | the flow needs a lower-commitment entry — a quiz or assessment as the transitional conversion | Extends docs/WEBSITE.md ## Lead Capture |
| hooked-ux | the conversion sticks but the next visit doesn't — post-conversion activation is the real leak | Extends 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.
| Mistake | Fix |
|---|---|
| Redesigning the step before measuring where the leak is | Run 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 words | Exit surveys, tickets, and sales calls (cro-methodology) — teams are almost always wrong about why visitors leave. |
| Polishing persuasion on top of an unclear message | Clarity before psychology: pass the 5-second test (storybrand-messaging) before adding proof and urgency. |
| Treating the offer as fixed and testing only cosmetics | The offer is the biggest lever (hundred-million-offers); a guarantee change outlifts a button change by orders of magnitude. |
| Faking scarcity or cherry-picking proof | Converts 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 early | Pre-commit sample size and duration, then report whatever comes back (cro-methodology, Kohavi). |
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:
docs/CONVERSION-OPTIMIZATION-PLAN.md is done, deferred: reason, or skipped: reason.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
SKILL.md and 2 other files (references) in conversion-optimization of wondelai/skills.
Open the folder on GitHubat commit c172996
Conversion Optimization next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Conversion Optimization this skillwondelai/skills | 2.4k | — | ~6.6k | Automated safety check: Pass | MIT | |
| FLOW SEO FrameworkAgriciDaniel/claude-seo | 18k | 2 repos | ~1.4k | Automated safety check: Pass | MIT | |
| Onboarding Crofreekmurze/dotfiles | 1k | 15 repos | ~1.6k | Automated safety check: Pass | None | |
| Google Analyticsthatrebeccarae/claude-marketing | 162 | 4 repos | ~1.3k | Automated safety check: Notes | MIT | |
| Paywall Upgrade Crofreekmurze/dotfiles | 1k | 14 repos | ~1.4k | Automated safety check: Pass | None | |
| Revenue Centric Designheliocosta-dev/revenue-centric-design | 740 | — | ~1.6k | Automated safety check: Pass | Custom licence |
AgriciDaniel/claude-seo
Brings the FLOW framework's stage-specific SEO prompts into the agent, from keyword discovery through backlinks, on-page work and conversion to local SEO, loaded on demand.
freekmurze/dotfiles
When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value.
thatrebeccarae/claude-marketing
Analyze Google Analytics data, review website performance metrics, identify traffic patterns, and suggest data-driven improvements.
freekmurze/dotfiles
When the user wants to create or optimize in-app paywalls, upgrade screens, upsell modals, or feature gates.
heliocosta-dev/revenue-centric-design
Playbook for designing SaaS and startup products that convert, retain, and monetize — landing pages & CRO, checkout & forms, onboarding/activation, churn reduction, pricing psychology, dashboards…
nowork-studio/notfair-plugin
Writes and improves title tags, meta descriptions, Open Graph and Twitter card tags for click-through, with character counts and A/B test variants.
wondelai/skills
Navigate the technology adoption lifecycle from early adopters to mainstream market.
wondelai/skills
Apply foundational design principles: affordances, signifiers, constraints, feedback, and conceptual models.
wondelai/skills
Run a structured 5-day process to prototype, test, and validate product ideas with real users.
wondelai/skills
Design habit-forming product loops using the Hook Model (Trigger, Action, Variable Reward, Investment).
wondelai/skills
Diagnose and fix retention problems using behavior design (B=MAP).
wondelai/skills
Design products and pricing around validated willingness to pay, from Ramanujam & Tacke's "Monetizing Innovation".
Categories
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.
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.
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.
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.
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.
Going by SKILL.md and its folder, Conversion Optimization needs the command-line tools its instructions call (npx). Our summary lists: Node.js.
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.
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.
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.
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.
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.
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.