Agent skill

Landing Optimizer

by aaron-he-zhu in aaron-he-zhu/aaron-marketing-skills

A skill your agent uses when the user asks to "optimize our landing page for influencer traffic", "fix our promo-code landing page", or "improve conversion from a creator campaign"; produces a…

Apache-2.0Auto-check passedMarketing & SEO

Install Landing Optimizer

skills CLI
$ npx skills add aaron-he-zhu/aaron-marketing-skills --skill landing-optimizer -a claude-code

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

GitHub CLI
$ gh skill install aaron-he-zhu/aaron-marketing-skills landing-optimizer --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/aaron-he-zhu/aaron-marketing-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/influencer/report/landing-optimizer .claude/skills/landing-optimizer && 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
landing-optimizer
GitHub stars
2.9k
Token cost
~3.3k tokens
SKILL.md length
1,426 words
Files
2 (incl. references)
Skills in repo
119
Repo updated
First seen
Licence
Apache-2.0

At a glance

A skill your agent uses when the user asks to "optimize our landing page for influencer traffic", "fix our promo-code landing page", or "improve conversion from a creator campaign"; produces a…

  • Works in 8 steps: Assess current state — capture campaign… → Evaluate message match — compare only a… → Page structure — recommend the… → …
  • The user asks to optimize our landing page for influencer traffic
  • SKILL.md covers Quick Start, Skill Contract, Data Sources and Instructions, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Landing Optimizer is an agent skill from aaron-he-zhu/aaron-marketing-skills. Use when the user asks to "optimize our landing page for influencer traffic", "fix our promo-code landing page", or "improve conversion from a creator campaign"; produces a message-match audit, page-structure and social-proof recommendations, a promo-code/CTA conversion plan, and an A/B test roadmap. Not for measuring campaign results after launch — use performance-analyzer. 落地页优化/达人流量转化提升

Its SKILL.md is about 3.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/templates.md`). Compatibility notes: Claude Code and compatible agent-skill hosts

It sits in Marketing & SEO, covering Influencer and creator marketing, Landing pages and A/B testing. The repository describes itself as: 120 marketing skills as an AI marketing staff — plugin, portable skills, or an 8-bot team across 7 disciplines (narrative, SEO/GEO, social, email, paid, influencer, launch) on… The licence is Apache-2.0.

When your agent uses it

  • The user asks to optimize our landing page for influencer traffic
  • Fix our promo-code landing page
  • Improve conversion from a creator campaign
  • Produces a message-match audit

Example prompts

  • “optimize our landing page for influencer traffic”
  • “fix our promo-code landing page”
  • “improve conversion from a creator campaign”
  • “/landing-optimizer”

Requirements

  • Compatibility (from SKILL.md): Claude Code and compatible agent-skill hosts

Workflow steps

8 steps, taken from the first numbered list in SKILL.md.

  1. Assess current state — capture campaign ref, transient page locator plus opaque page/snapshot refs, traffic source, current conversion…
  2. Evaluate message match — compare only a creator message cleared by the reuse gate against the supplied page snapshot across message, value…
  3. Page structure — recommend the influencer-traffic layout (hero → social proof → product → more proof → FAQ → final CTA) and give…
  4. Social proof integration — use a creator name, quote, asset, embed, screenshot, badge, or testimonial only when its exact frozen approval…
  5. Conversion optimization — tune CTA copy/placement, design the promo-code experience (auto-apply via URL param, prominent display…
  6. A/B testing plan — rank supported tests by impact/effort, then write at least one hypothesis with variants, sample size, duration, and…
  7. Influencer-specific pages — decide whether a dedicated creator page is warranted. A creator name in the path or page, creator-linked…
  8. Performance tracking — set targets for load time, bounce, CR, add-to-cart, AOV; define UTM params and events for attribution.

What it can do on your machine

Read from SKILL.md and the folder at commit d5529cb. 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

    No scripts in the folder and no shell commands in SKILL.md.

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

  • Network

    No URLs in SKILL.md.

    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.

  • Compatibility

    Claude Code and compatible agent-skill hosts

    From compatibility in the SKILL.md frontmatter.

Context cost

Landing Optimizer loads about 3.3k tokens when it runs, and up to ~7.9k if it reads all its reference files. Until then it costs about 103 tokens; SKILL.md has 1,426 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~103
When it runs · the whole SKILL.md, loaded when a task matches
~3.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~7.9k

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 aaron-he-zhu/aaron-marketing-skills at commit d5529cb, republished under its Apache-2.0 licence (© aaron-he-zhu). 1,426 words, ~3,263 tokens.

Download SKILL.mdSave it as .claude/skills/landing-optimizer/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
landing-optimizer
description
Use when the user asks to "optimize our landing page for influencer traffic", "fix our promo-code landing page", or "improve conversion from a creator campaign"; produces a message-match audit, page-structure and social-proof recommendations, a promo-code/CTA conversion plan, and an A/B test roadmap. Not for measuring campaign results after launch — use performance-analyzer. 落地页优化/达人流量转化提升
compatibility
Claude Code and compatible agent-skill hosts
slug
landing-optimizer
displayName
Landing Optimizer · 落地页优化
summary
流量落地页转化优化:信息匹配、首屏、CTA 与信任要素
version
20.1.0
license
Apache-2.0
homepage
https://github.com/aaron-he-zhu/aaron-marketing-skills
when_to_use
Activate when the user wants to build or improve a landing page that receives influencer-driven traffic: message match between creator content and the page…
argument-hint
<landing page URL or campaign> [influencer handle] [promo code]
metadata.author
aaron-he-zhu
metadata.version
20.1.0

Landing Optimizer

This skill helps you create and optimize landing pages specifically for influencer marketing traffic. When users click from an influencer's post, the landing experience should feel connected and optimized for conversion.

Cross-discipline (paid ads): this is also the paid-ads post-click skill — the page half of the ROAS Offer message-match (it pairs with ad-creative-builder, which owns the ad half). The same diagnose-and-fix flow applies to paid landing pages; save paid runs under memory/ad/landing-optimizer/. On paid runs, message-match the page against the offer-claims-registry ledger when present: offer terms, promo codes, and dates against memory/claims/offers.md, and claim wording against the approved variants in memory/claims/claims-ledger.md.

Quick Start

Shortest invocation:

Optimize our landing page for traffic from [influencer campaign]

Common scenario — diagnose and fix a low-converting creator page:

Our influencer landing page has [X%] conversion rate. How can we improve it?

Skill Contract

  • Reads: a transient landing-page locator plus opaque page_ref/snapshot ref and current state, conversion rate and goal, traffic source, stable opaque creator_ref, platforms/content type, and any proposed creator display name, message, quote, asset, embed, or screenshot. Every creator reuse also reads the exact frozen approved_asset_ref plus creator-content-auditor approval_ref, and a rights record that is active, dated/evidenced, unexpired, and explicitly scoped to channel, territory, format, duration, and paid-vs-organic use. Inputs come from the user when no tool is connected.
  • Writes: return the optimization plan inline by default; save it to memory/influencer/landing-optimizer/YYYY-MM-DD-<topic>.md (or the declared paid path) only with exact WARM-save authorization. Saved artifacts and handoffs keep creator_ref, page_ref, snapshot_ref, frozen asset/approval refs, and opaque rights/evidence refs only—never a raw creator handle/name, profile/content/page URL, email, provider ID, or embedded creator media.
  • Promotes: only with separate exact authorization, promote durable facts — active campaign ref, opaque page ref, baseline conversion rate, promo code ref, primary creator_ref — to memory/hot-cache.md.
  • Done when:
    • Message-match score and named fixes are produced for the page.
    • A prioritized conversion plan (CTA, promo-code experience, friction, mobile) exists with evidence-labeled impact or Unknown/NEEDS_INPUT.
    • An A/B test roadmap with at least one hypothesis and success metric is written.
    • Every proposed creator name/quote/asset/embed/screenshot reuse has the exact frozen auditor approval and an active dated scoped-rights row covering the whole implementation/test duration; blocked reuse remains NEEDS_INPUT and is neither copied nor tested.
  • Primary next skill: performance-analyzer — measure whether the optimizations moved conversion.
Handoff Summary

Emit the standard shape from skill-contract.md §Handoff Summary Format.

Data Sources

This family needs no live integrations (Tier 1). The skill works from a transient page locator, current conversion data, opaque creator/page/evidence refs, approved messaging, and the rights inputs supplied by the user. A brief, draft, public post, or contract label does not substitute for the exact frozen creator-content-auditor approval plus current scoped-rights evidence.

Optional connectors that can deepen the analysis when available:

  • ~~analytics — pull live conversion rate, bounce rate, scroll depth, and add-to-cart events instead of asking.
  • ~~A/B testing platform — read past test results and feed sample-size/duration estimates.
  • ~~CMS / landing page builder — inspect current page structure and copy directly.
  • ~~social platform analytics — confirm the creator's actual messaging and audience.

See CONNECTORS.md for the verified free/keyless recipe per category. Every step degrades gracefully to user-supplied inputs.

Instructions

When a user requests landing page help, work through these steps. Each step's fill-in template, ASCII layout, and HTML snippet live in references/templates.md — keyed by the same step numbers.

Creator-reuse gate: before copying, proposing, publishing, or testing any creator display name, quote, claim excerpt, video, image, thumbnail, embed, screenshot, badge, testimonial, creator-specific path, or creator-linked tracking token, require all of the following for that exact reuse: stable opaque creator_ref; exact frozen approved_asset_ref; matching creator-content-auditor approval_ref with approved status for that version; rights status active; status_observed_at; opaque status_evidence_ref; unexpired start/end or perpetual duration; and explicit channel, territory, format, duration, and paid | organic | both scope matching the page and its entire proposed experiment/flight. Resolve any permitted display name or media locator only transiently at implementation. If any field is missing, stale, non-active, expired during the proposed test, disputed, revoked, unknown, or out of scope, return NEEDS_INPUT for that reuse and do not copy the name/quote, embed or screenshot the asset, publish a variant, or start a test. You may still audit non-creator page elements with opaque snapshot refs and propose generic placeholders.

  1. Assess current state — capture campaign ref, transient page locator plus opaque page/snapshot refs, traffic source, current conversion rate, goal, and the traffic context (creator_ref, platforms, content type, approved message ref, promo code ref, audience). Keep raw locators transient.
  2. Evaluate message match — compare only a creator message cleared by the reuse gate against the supplied page snapshot across message, value prop, offer, product, and tone; produce a Message Match Score (X/10) and named fixes. If the frozen approval or rights row is missing, keep the creator side Unknown, return NEEDS_INPUT, and do not quote or paraphrase it into page copy. For paid runs, also verify the page's offer/promo terms against memory/claims/offers.md when the ledger exists — an ad's "50% off" promise is only true while the offer row is live.
  3. Page structure — recommend the influencer-traffic layout (hero → social proof → product → more proof → FAQ → final CTA) and give section-by-section fixes. Any creator-specific slot stays an opaque placeholder until the reuse gate passes.
  4. Social proof integration — use a creator name, quote, asset, embed, screenshot, badge, or testimonial only when its exact frozen approval and rights scope pass; otherwise omit it and return NEEDS_INPUT. Apply the same gate separately to every additional creator.
  5. Conversion optimization — tune CTA copy/placement, design the promo-code experience (auto-apply via URL param, prominent display, confirmation), cut friction, and check mobile (load speed, thumb-friendly CTA, scroll depth).
  6. A/B testing plan — rank supported tests by impact/effort, then write at least one hypothesis with variants, sample size, duration, and success metric. Do not include or start a creator-name/asset/quote variant unless the approved rights duration covers the full planned test and resulting publication period.
  7. Influencer-specific pages — decide whether a dedicated creator page is warranted. A creator name in the path or page, creator-linked tracking token, and every personalized asset each require the reuse gate; otherwise use a generic campaign page and opaque tracking ref.
  8. Performance tracking — set targets for load time, bounce, CR, add-to-cart, AOV; define UTM params and events for attribution.

Return the finished plan inline. Offer memory/influencer/landing-optimizer/YYYY-MM-DD-<topic>.md (or memory/ad/landing-optimizer/ for paid runs) for exact WARM-save authorization, and ask separately before any HOT promotion. Before save/handoff, replace raw creator identities, media/page/profile URLs, and copied creator text with opaque refs; the persisted plan resolves nothing directly.

Show full SKILL.md (374 more words)Show less

Example

User: "Our dated analytics export shows 1.2% CR versus our source-dated 2–3% target. Use creator_ref: creator-042, approved_asset_ref: asset-v7, and its frozen creator-content-auditor approval_ref. The supplied rights row is active, observed today with an opaque evidence ref, and covers US web landing-page display of the approved name, exact quote, video embed, and screenshot formats for both paid and organic traffic through the full six-week test/flight. The approved asset says 'smooth texture'; the page snapshot leads with 'high protein', omits the video, does not auto-apply the promo, and places the mobile CTA below the fold. Build a plan."

Output (abridged — full version in references/templates.md):

  • Diagnosis: 1.2% CR, below the supplied 2–3% target for influencer traffic.
  • Issues: message mismatch (the frozen approved asset says "smooth texture", while the page snapshot leads with "high protein"); the approved creator asset is absent; the promo is not auto-applied; the mobile CTA is below the fold.
  • Priority fixes: test the exact frozen approved video in the hero within its active scoped rights, auto-apply the promo, match the headline to approved wording, and move the mobile CTA above the fold. Any lift is Unknown until the predeclared A/B test reaches its decision rule; do not add isolated lift estimates into a promised CR.
  • Test plan: wk1 hero changes, wk2 headline A/B, wk3 CTA copy.

Reference Materials

  • templates.md — all step fill-in templates, ASCII layouts, HTML snippets, the full worked example, and tips.

  • skill-contract.md — shared contract and Handoff Summary format.

  • state-model.md — memory tiers and save-path conventions.

  • CONNECTORS.md — free/keyless data recipes per connector category.

  • conversion-quality.md — advisory conversion rubric (non-veto) to sanity-check the optimization plan.

  • Sibling skills in the influencer-marketing family:

Next Best Skill

Primary: performance-analyzer — measure whether the optimizations actually moved conversion, AOV, and attribution.

Alternates (same Report family):

  • content-amplifier — when the audit shows the page needs more creator content to feature.
  • roi-calculator — when the page's conversion is validated and you want to translate it into ROI and payback math.

Termination note: Maintain a visited-set this session. If a recommended skill has already been invoked, stop and report the chain as complete rather than re-running it. Hard stop at chain depth 3 to avoid loops.

© aaron-he-zhu, Apache-2.0. 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 1 other file (references) in influencer/report/landing-optimizer of aaron-he-zhu/aaron-marketing-skills.

  • SKILL.md
  • references/templates.md

Open the folder on GitHubat commit d5529cb

Compare with similar skills

Landing Optimizer 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.

Landing Optimizer compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Landing Optimizer this skillaaron-he-zhu/aaron-marketing-skills2.9k—~3.3kAutomated safety check: PassApache-2.0
Landing Optimizeraiskillstore/marketplace433—~2.3kAutomated safety check: PassApache-2.0
Page Croborghei/Claude-Skills891—~5.9kAutomated safety check: PassMIT
Autoresearchericosiu/ai-marketing-skills3.6k2 repos~2.2kAutomated safety check: PassMIT
Brand Kitcognyai/claude-code-marketing-skills104—~3.4kAutomated safety check: NotesNone
Google Ads Landing ReviewTheMattBerman/google-ads-copilot238—~4.1kAutomated safety check: PassMIT

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Questions about Landing Optimizer

What does Landing Optimizer do?

A skill your agent uses when the user asks to "optimize our landing page for influencer traffic", "fix our promo-code landing page", or "improve conversion from a creator campaign"; produces a…. Landing Optimizer is an agent skill from aaron-he-zhu/aaron-marketing-skills. Use when the user asks to "optimize our landing page for influencer traffic", "fix our promo-code landing page", or "improve conversion from a creator campaign"; produces a message-match audit, page-structure and social-proof recommendations, a promo-code/CTA conversion plan, and an A/B test roadmap.

When should I use Landing Optimizer?

Landing Optimizer fits situations like: the user asks to optimize our landing page for influencer traffic; fix our promo-code landing page; improve conversion from a creator campaign; produces a message-match audit.

How do I install Landing Optimizer in Claude Code?

Run `npx skills add aaron-he-zhu/aaron-marketing-skills --skill landing-optimizer -a claude-code`. Or copy the skill folder (influencer/report/landing-optimizer in aaron-he-zhu/aaron-marketing-skills) into .claude/skills/landing-optimizer in your project. Claude Code loads it when a task matches its description.

How do I install Landing Optimizer in Codex?

Run `npx skills add aaron-he-zhu/aaron-marketing-skills --skill landing-optimizer -a codex`. Or copy the skill folder (influencer/report/landing-optimizer in aaron-he-zhu/aaron-marketing-skills) into .agents/skills/landing-optimizer in your project. Codex loads it when a task matches its description.

Can I use Landing Optimizer 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 aaron-he-zhu/aaron-marketing-skills --skill landing-optimizer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/landing-optimizer, .gemini/skills/landing-optimizer, .github/skills/landing-optimizer and .opencode/skills/landing-optimizer in your project.

What does Landing Optimizer need to run?

SKILL.md names no scripts, command-line tools or credentials: Landing Optimizer is instructions for the agent only. Compatibility (from SKILL.md): Claude Code and compatible agent-skill hosts.

Does Landing Optimizer access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Landing Optimizer 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 Landing Optimizer use?

Landing Optimizer is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Landing Optimizer use?

About 3.3k tokens (SKILL.md is roughly 13k 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 4.7k tokens, read only when the agent opens those files.

What are the alternatives to Landing Optimizer?

Skills that share tags, products or a category with Landing Optimizer: Landing Optimizer (aiskillstore/marketplace, 433 stars), Page Cro (borghei/Claude-Skills, 891 stars), Autoresearch (ericosiu/ai-marketing-skills, 3.6k stars) and Brand Kit (cognyai/claude-code-marketing-skills, 104 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Landing Optimizer?

aaron-he-zhu (a GitHub user) maintains it in aaron-he-zhu/aaron-marketing-skills, which has 2,898 GitHub stars. The repository holds 119 skills in this directory. The repository was last updated on October 11, 2026.

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