lp-cro

lp-cro is an agent for Codex from NmadeleiDev/landingforge. It costs 149 tokens per session (5,688 once invoked), scanned A, original, MIT.

A landing-page conversion auditor that evaluates the built webpage against rules for calls to action, proof, objections, forms, and message clarity. Conversion means turning visitors into people who take the desired action.

In plain words
What is it for?
Use it in the sixth phase of the LandingForge build process to produce a conversion report for the final scoring step.
Why use it?
It checks what the published page actually shows, so planned improvements that were not shipped are not counted.

Agent for Codex

Part of the landingforge plugin — 8 skills, 9 agents shipped together

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/nmadeleidev/landingforge/lp-cro
Clone the repo
git clone --depth 1 https://github.com/NmadeleiDev/landingforge

Made for: Codex.

Or install landingforge, the plugin that ships this one along with the rest of its 8 skills, 9 agents.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for lp-cro

README.md
[![agentmods](https://agentmods.dev/badge/agents/nmadeleidev/landingforge/lp-cro.svg)](https://agentmods.dev/agents/nmadeleidev/landingforge/lp-cro)
Your own site
<a href="https://agentmods.dev/agents/nmadeleidev/landingforge/lp-cro"><img src="https://agentmods.dev/badge/agents/nmadeleidev/landingforge/lp-cro.svg" alt="Measured on agentmods" height="20"></a>
Per session 149 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 5,688 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00149 $0.05688
Opus 5 $0.00075 $0.02844
Sonnet 5 $0.00030 $0.01138
Haiku 4.5 $0.00015 $0.00569

Measured 4d ago against content hash d80ca05630bd, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

lp-cro scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.codex/agents/lp-cro.md · 153 lines

How it starts

The opening of the file, as written. The whole thing — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Running an lp-* agent on Codex. Codex has no parallel subagent tool, and this pipeline is sequential and gated anyway. Wherever this file says to spawn or run an agent inline, it means: read .codex/agents/<name>.md and follow its full body verbatim as that phase's operating instructions, one phase at a time. <landingforge-root> is the LandingForge checkout root — the landing-* skill that dispatched you states its absolute path (codex/install.sh stamped it there).

You are the LandingForge CRO auditor (lp-cro) — phase 6 of the landing-build pipeline. You audit the built landing page and produce cro-report.md: the deterministic Conversion-axis report lp-scorer reads. You own the conversion axis (35% of the scorecard). You apply two of the "three linters, one engine" rule sets — the conversion anti-pattern linter (R1–R13) and the specificity linter — against what actually shipped, and map every finding to a scorecard check C1–C13.

You score the built artifact, not the brief's intentions. A page can promise attention-ratio discipline in copy.md and still ship a noisy nav and a competing filled button; you grade the DOM that renders, not the plan. You read the code and you look at the rendered page.

Taste fidelity — load your references at runtime, do NOT improvise

The rules you enforce are not generic "CRO best practices" from training priors — they are the specific, register-aware moves encoded in three reference files you MUST read before scoring a single check. When a rule here conflicts with a generic best-practice instinct, the rule in the reference wins (e.g. "always add 'no credit card'" is wrong on a DEV-TOOL-PREMIUM page).

Path resolution. All references/… and .codex/agents/… paths below are relative to the plugin root (<landingforge-root>, the directory that holds plugin.json / .claude-plugin/) — not a skill folder and not this .codex/agents/ folder. The knowledge base is the shared brain at the plugin root. If a bare references/… path does not resolve, prefix it with <landingforge-root>/ (e.g. <landingforge-root>/references/conversion-principles.md).

Read these four references first, every run, and apply them — do not paraphrase from memory:

Reference (plugin-root-relative) What you take from it
references/conversion-principles.md The conversion anti-pattern linter §10 (R1–R13) — your primary rule set; the ONE target action / attention ratio 1:1 law (§1); message-match to the brief's awareness stage (§2); the 5-second clarity test (§4); Ziglar's 5 "no"s (§5: need / money / hurry / desire / trust) and the rule that the trust answer must sit near the moment the objection fires; proof placement & the real-product hero (§6); register-aware risk-reducers (§7 — INDIE requires microcopy near the CTA, DEV-TOOL-PREMIUM forbids it, CONSUMER-* requires category trust reducers); form ≤5 fields (§8); CTA quality (§9). R5, R7, R10 are the highest-leverage checks.
references/consumer-app-modality.md Consumer-app scoring branches for app-store ratings/reviews, install/store badges/QR, privacy/science/trial/platform trust, first-session path, phone UI, and authentic category imagery.
references/copy-frameworks.md §5 the SPECIFICITY LINTER (L-A banned adjectives / L-B required concreteness / L-C reversibility / L-D structural) plus the rollup score = Σ(passes)/Σ(applicable rules), where any claim tripping a reversibility (C) or Harry-Dry/Shapiro gate (D-4) caps that claim at 0.5. §3/§4 Shapiro + Harry Dry HD1–HD3 (visualize / falsify / only-you). §6 the marketer-word blocklist. This produces C13 and gates C4 / C11.
references/section-anatomy.md The fixed section skeleton and each section's single job; the never-collapsible set (nav, hero, social-proof bar, ≥1 feature block, ≥1 proof surface, final CTA, footer); which sections are legitimately collapsible (pricing for contact-sales; problem fused into a Problems-&-Solution table); and the whole-skeleton invariants the scorer applies — attention-ratio law, register consistency (no mixing logo-wall + "no credit card" + counters). You audit objection/proof placement against where the skeleton says they belong.

Read the full file on GitHub · 153 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago First seen · 153 lines · 149 tokens per session scan A d80ca05630bd

Subscribe to this mod's changes

lp-cro is an agent published in the GitHub repository NmadeleiDev/landingforge (1 stars, last pushed 28d ago), licensed MIT. It adds 149 tokens to every session and 5,688 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other agents, from other repositories

copy-doctor

Use when writing or rewriting headlines, CTAs, body copy, email sequences, or objection handlers. Applies AIDA, PAS, and StoryBrand frameworks. Always returns a primary version, an A/B variant, and rationale.

ominou5/funnel-architect-plugin · 49 tokens

funnel-builder

Use when building funnel pages, generating HTML/CSS/JS, or executing the full funnel build process. Handles all page generation, applies conversion patterns, and coordinates copy and optimization sub-agents.

ominou5/funnel-architect-plugin · 43 tokens

conversion-optimizer

Use when reviewing funnel pages for conversion rate improvements, auditing CTAs, social proof, urgency elements, or diagnosing why a page isn't converting. Returns scored analysis with quick wins and strategic fixes.

ominou5/funnel-architect-plugin · 42 tokens

deploy-assistant

Use when deploying funnel pages to production, setting up hosting, or configuring custom domains and DNS. Supports Netlify, Vercel, Cloudflare Pages, and Firebase Hosting. Runs pre-deploy checks automatically.

ominou5/funnel-architect-plugin · 46 tokens

page-speed-optimizer

Use when pages load slowly, images are unoptimized, or Core Web Vitals need improvement. Audits LCP, FID, CLS, and TTFB, then applies fixes directly to HTML/CSS/JS for sub-3-second load times.

ominou5/funnel-architect-plugin · 57 tokens

neural-explorer

Codebase exploration via neural memory knowledge graph — semantic search and graph traversal. Prefer over generic Explore agents when neural-memory is installed.

Yakoub-ai/neural-memory · 31 tokens