Mokhai – Agent Readiness Kit
by Mohamed Khaled 0 (0 reviews)

Mokhai – Agent Readiness Kit

Publish a clean Markdown version of every page for AI agents — linked from llms.txt with per-page descriptions — plus schema and a readiness score.

Mokhai ranks #61,684 among WordPress.org plugins with 0+ active installations, is #3,076 of 4,265 in the SEO & Marketing category, and was last updated Jul 24, 2026. Data from WordPress.org, refreshed twice daily — see methodology.

Tested up to WP 7.0.8 (Current: 7.1.4)
v0.8.1 Current Version v0.8.1
Updated 3 months ago Last Update on 24 Jul, 2026
Refreshed 1 week ago Last Refreshed on
#3,076 of 4,265 in SEO & Marketing Downloads -46.2% this week
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Rank
#61,684
— No change
Active Installs
0+
-100%
KW Avg Position
N/A
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Downloads
654
+2 today
Support Resolved
0%
— No change
Rating
0%
Review 0 out of 5
0 (0 reviews)

Next Milestone 10

Total Progress 20%
0+ 10+
34,116
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-
Growth Needed
8,000,000
Active Installs
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Rank Changes

58,600 60,142 61,684 63,226 64,768 31-10-2026 01-11-2026 02-11-2026 03-11-2026 04-11-2026 05-11-2026 06-11-2026 07-11-2026
49,441 53,616 57,790 61,964 66,139 23-10-2026 24-10-2026 25-10-2026 26-10-2026 27-10-2026 28-10-2026 29-10-2026 30-10-2026 31-10-2026 01-11-2026 02-11-2026 03-11-2026 04-11-2026 05-11-2026 06-11-2026 07-11-2026
Current #61,684
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Active Installs Growth

Active Installs 0,000,000+
Growth +0.0%
Peak 0,000,000

Downloads Growth

0 10 31-10-2026 01-11-2026 02-11-2026 03-11-2026 04-11-2026 05-11-2026 06-11-2026 07-11-2026
0 10 20 23-10-2026 24-10-2026 25-10-2026 26-10-2026 27-10-2026 28-10-2026 29-10-2026 30-10-2026 31-10-2026 01-11-2026 02-11-2026 03-11-2026 04-11-2026 05-11-2026 06-11-2026 07-11-2026
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Reviews & Ratings

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Frequently Asked Questions

Common questions about Mokhai – Agent Readiness Kit

AI assistants like ChatGPT, Claude, and Perplexity increasingly visit websites to answer questions for their users. Most WordPress themes serve them the same heavy HTML built for humans — menus, sliders, widgets — and the actual content gets lost in the noise. llms.txt is a simple convention: a plain-text file at your site's root (like robots.txt, but for content) that tells AI assistants what your site is about and where to find your best pages. Mokhai generates and maintains it for you, alongside clean Markdown versions of your pages that agents can actually read. If AI assistants are answering questions in your topic area, this determines whether your site is the source they cite — or the one they skip.
No. Every deterministic surface (Markdown Views, /llms.txt floor, rule-based Context Score narrative, gap-fill JSON-LD emission) runs fully locally with no external calls. Modules that benefit from an LLM (the Markdown cleanup pass, /llms.txt entry-description drafting, the LLM-narrated Context Score) require the optional WP AI Client to be configured, but each is independently toggleable and not load-bearing for the core agent-readiness contract.
For JSON-LD: when an SEO plugin (Yoast, Rank Math, AIOSEO, The SEO Framework) is active, Mokhai emits nothing competing — schema is theirs. When no SEO plugin is emitting JSON-LD, you can optionally enable Mokhai's native gap-fill emission from the Context Profile. For noindex: Mokhai auto-detects per-post noindex from Yoast, Rank Math, and AIOSEO and drops the post from agent surfaces. Use the mokhai_post_is_noindexed filter to add support for additional sources.
/llms.txt is one surface among several. Mokhai ships the integrated reading layer (Markdown views), the discovery layer (/llms.txt with editorial entries and LLM-powered descriptions), the audit layer (Context Score across seven sub-scores), and the schema coordination layer as a single coherent unit driven by one Context Profile. Most existing plugins target one of these surfaces in isolation; Mokhai treats them as a coordinated stack.
v0.5.0 is the public-launch baseline: Markdown Views, /llms.txt, the Context Score, the AI Assistant Preview pane, and the WordPress Abilities API + MCP integration. Looking ahead: agent-activity analytics (see which AI agents visit your site, not just optimize for them), a fuller agent-actionable layer (callable tools via WebMCP / navigator.modelContext), and a richer /.well-known/llms-policy.json policy-declaration surface.

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