# Inside LAXIMA: The Six Free AI Tools, the Signal Brief, and the Blog That Power Our Site > A field guide to everything LAXIMA ships for free - six AI tools, the four-hour Signal brief, and the GEO/AEO-shaped blog engine behind them. **Author:** LAXIMA Team **Published:** 2026-05-26 **Updated:** 2026-05-26 **Reading time:** 9 min **Category:** ai automation **Tags:** LAXIMA, AI Tools, LLM Picker, AI ROI Calculator, AI Readiness, Prompt Library, AI Signal, GEO, AEO **Canonical URL:** https://laxima.tech/blog/inside-laxima-tools-signal-blog --- LAXIMA is an AI automation agency, but most of the surface area of our site is not a sales page. It is a public toolkit: six interactive tools, a continuously refreshed AI news brief, and a blog engine built to be read by humans and cited by AI search alike. All of it is free, no sign-up, no email gate. This post is a single, navigable map of every feature we ship — what each tool does, who it is for, and how the pieces connect. **The short answer:** LAXIMA's public product is a set of decision tools ([LLM Picker](https://laxima.tech/tools/llm-picker), [Context Window Fit Checker](https://laxima.tech/tools/context-window-fit), [AI Readiness Assessment](https://laxima.tech/tools/ai-readiness-assessment), [AI ROI Calculator](https://laxima.tech/tools/ai-savings-calculator), [AI Prompt Library](https://laxima.tech/tools/library), and the open-source [LAXIMA Skills Marketplace](https://github.com/laxima-tech/laxima-skills)) plus the [AI Signal](https://laxima.tech/signal) brief and the LAXIMA blog. ## The six free tools The tools live under `/tools`. Each one is a server-rendered page with the static answer above the fold and an interactive widget below. That structure is deliberate — it is how the pages get cited by AI Overviews, ChatGPT, and Perplexity without forcing a JavaScript render. ### 1\. LLM Picker — answer 7 questions, get a shortlist The [LLM Picker](https://laxima.tech/tools/llm-picker) is a seven-question quiz that produces a ranked shortlist of large language models for a specific project. It covers Claude (Anthropic), GPT (OpenAI), Gemini (Google), Llama (Meta), Mistral, DeepSeek, and other frontier and open-weight models. What makes it useful: - **Cost estimates at your real volume.** You enter expected monthly tokens; the picker converts model pricing into a monthly number for each candidate. - **Reasoning, not just ranks.** Every recommendation comes with the trade-off behind it — context window size, speed, quality tier, hosting model, vendor lock-in. - **Programmatic sub-pages.** The picker exposes `/for/[useCase]` pages (e.g. coding, summarization, long-context analysis), `/compare/[pair]` head-to-head pages, and `/model/[id]` profiles. Each one is indexable, deep-linkable, and shareable with a custom OG image baked from the URL. The underlying model catalog is curated by hand against a strict quality bar — frontier-tier or proven best-in-class for a niche, cross-referenced against LMArena Elo and Artificial Analysis. We do not list models that fail to place in any independent ranking. ### 2\. Context Window Fit Checker — will your prompt fit? The [Context Window Fit Checker](https://laxima.tech/tools/context-window-fit) answers a question every developer hits sooner or later: _will this fit in the model's context window, and what will it cost per call?_ Paste text, or drop a `.txt`, `.md`, `.pdf`, or `.docx` file. The tool tokenizes it locally in your browser, then compares the token count against 20+ frontier LLM context windows and computes the input cost per call at current pricing. Two things worth calling out: - **Nothing is uploaded.** Tokenization, file parsing, and cost math all run client-side. No server, no telemetry attached to your file. - **Per-model cost, not a single estimate.** The same prompt can be twenty times more expensive on one model than another. The checker makes that comparison concrete in dollars, not abstract in "tokens." ### 3\. AI Readiness Assessment — 24 questions, 6 dimensions The [AI Readiness Assessment](https://laxima.tech/tools/ai-readiness-assessment) is a 24-question quiz across six dimensions: data, process, technology, team, strategy, and budget. It returns a readiness score and a written roadmap. The output is intentionally diagnostic, not prescriptive. Most failed AI initiatives are not failed model picks — they are organizations attempting automation on top of dirty data, unclear ownership, or KPIs that reward the wrong behavior. The assessment surfaces which of those six axes is the actual bottleneck, before any tool selection happens. ### 4\. AI ROI Calculator — estimate your real savings The [AI ROI Calculator](https://laxima.tech/tools/ai-savings-calculator) takes three numbers from your team — headcount, automatable hours per week, fully-loaded hourly cost — and returns annual savings, five-year ROI, and a realistic estimate of implementation cost. It is built on the same accounting we use to scope client engagements: labor cost replaced minus implementation cost minus ongoing model and tooling cost, projected over five years with adoption ramp. The point is to make the "is this worth doing?" conversation quantitative in under a minute. ### 5\. AI Prompt Library — copy-paste prompts that work The [AI Prompt Library](https://laxima.tech/tools/library) is a curated collection of business-grade prompts organized by function — sales, marketing, customer support, data analysis, HR, operations, strategy, and more. Every prompt is copy-paste ready and works in ChatGPT, Claude, Gemini, and any major chat assistant. The library has both a hub view and indexable per-prompt and per-category pages, so individual prompts are deep-linkable and discoverable by search engines and AI assistants. Search, filter by category or use case, copy. ### 6\. LAXIMA Skills Marketplace — open-source skills for Claude Code The [LAXIMA Skills Marketplace](https://github.com/laxima-tech/laxima-skills) is open-source. It is a growing set of ready-made **skills** for Claude Code — packaged capabilities that extend a coding agent with concrete workflows like branding, frontend design research, browser testing, team-update generation, and more. Install in one command from inside Claude Code: `/plugin marketplace add laxima-tech/laxima-skills` Skills are the cleanest unit of agent extension we have found: small, scoped, declarative, and free of the runtime fragility of plugins. The marketplace is where we open-source the ones we build for client work that are general enough to be useful to other teams. ## AI Signal — a curated brief, refreshed every four hours The [AI Signal](https://laxima.tech/signal) page is a continuously refreshed brief of the most important AI and tech stories, aggregated from Hacker News, GitHub trending, and Hugging Face / Replicate model releases. What makes it different from a generic feed: - **Composite ranking.** Items are scored with `trend_score × 100 + log(raw_score) × 5 − staleness_penalty`, so a fresh repository with rapid star velocity can outrank an older story with higher absolute numbers. - **Heat tiers and freshness flags.** Three flame glyphs and three freshness states (_live_, _cooling_, _frozen_) make signal strength legible at a glance. - **Open subscriptions.** The brief is available as a webpage, an [RSS feed](https://laxima.tech/signal/feed.xml), a [JSON Feed](https://laxima.tech/signal/feed.json), and a plain Markdown render at [/signal.md](https://laxima.tech/signal.md) so LLM agents can ingest it without scraping. - **Refresh cadence.** The list rebuilds every four hours via a scheduled cron, with on-page countdown to the next refresh and a 60-minute revalidation window on the public page. Signal is hub-only by design — individual items do not get their own indexable pages. The brief itself is the artifact. ## The blog — built for humans and for AI citations The LAXIMA blog is where our long-form thinking lives. Posts cover AI automation, workflow redesign, agentic systems, case studies, and the operational details of running an AI-first agency. From a reader's perspective it is a normal blog. Under the hood it is built to a specific specification: - **Server-rendered content.** Every post is HTML at the URL — no client-side fetch gating the primary text. AI crawlers see what readers see. - **Markdown export for every post.** Each article is available at `/blog/.md` as clean Markdown, so an LLM agent can consume the post without parsing HTML. This is wired into our `llms.txt` manifest at [laxima.tech/llms.txt](https://laxima.tech/llms.txt). - **Schema-rich metadata.** Posts emit `Article`, `BreadcrumbList`, and `FAQPage` JSON-LD where applicable. Q&A blocks inside articles are both visible HTML and structured data. - **Dynamic sitemap and IndexNow.** [sitemap.xml](https://laxima.tech/sitemap.xml) revalidates hourly. On publish, we push the new URL to IndexNow so Bing, Yandex, and participating engines see it within seconds. - **RSS, JSON Feed, video sitemap.** Standard feeds ([/feed.xml](https://laxima.tech/feed.xml), [/feed.json](https://laxima.tech/feed.json)) plus a video sitemap for embedded media. The admin panel has a built-in LLM article generator that scrapes 2–5 source URLs, builds a link corpus of our existing posts, and produces a structured draft. A plagiarism gate refuses any output that copies an 80-character sentence from a source verbatim. Generation is a starting point — every published post is reviewed and edited by a human. ## How the pieces fit together The reason there are so many small free things is that LAXIMA is bet on Generative Engine Optimization (GEO) and AI Engine Optimization (AEO). The wager: in the next two years, more business-critical questions will be answered by AI assistants than by ten-blue-link search results. Each tool is a self-contained, citable answer to a specific question someone might ask an AI. - _"Which LLM should I use for \[X\]?"_ → LLM Picker. - _"Will this fit in \[model\]'s context window?"_ → Context Window Fit Checker. - _"Is my business ready for AI?"_ → Readiness Assessment. - _"How much could AI save us?"_ → ROI Calculator. - _"What's the best prompt for \[task\]?"_ → Prompt Library. - _"What's hot in AI today?"_ → Signal. - _"How should we think about \[longer topic\]?"_ → Blog. Every tool, brief, and post is built so the answer is visible in the HTML, the FAQ is structured, the schema is valid, and the Markdown is one URL away. We use the same skills and conventions on client engagements — the public site is the open-source version of the agency's internal toolkit. ## Where to start If you are looking at LAXIMA for the first time and want a thirty-second tour: - Start with the [Readiness Assessment](https://laxima.tech/tools/ai-readiness-assessment) if you are scoping an AI initiative inside an organization. - Start with the [LLM Picker](https://laxima.tech/tools/llm-picker) or [Context Window Fit Checker](https://laxima.tech/tools/context-window-fit) if you are an engineer choosing models for a build. - Start with the [ROI Calculator](https://laxima.tech/tools/ai-savings-calculator) if you are building the business case. - Subscribe to [Signal](https://laxima.tech/signal) if you want to keep up with frontier AI without doomscrolling Hacker News. - Browse [the blog](https://laxima.tech/blog) for the deeper thinking behind how we build. If you want the toolkit we use inside Claude Code, the [Skills marketplace](https://github.com/laxima-tech/laxima-skills) is on GitHub. ### What tools does LAXIMA offer for free? LAXIMA ships six free tools: the LLM Picker (quiz-based model shortlist), the Context Window Fit Checker (token + cost estimator for pasted text or uploaded files), the AI Readiness Assessment (24-question 6-dimension business diagnostic), the AI ROI Calculator (annual savings and 5-year ROI), the AI Prompt Library (curated business prompts), and the open-source LAXIMA Skills Marketplace for Claude Code. None require sign-up. ### What is LAXIMA Signal? LAXIMA Signal is a curated AI and tech news brief that refreshes every four hours. It aggregates Hacker News, GitHub trending, and Hugging Face / Replicate releases, then ranks items by a composite of trend velocity, raw score, and staleness. It is available as a webpage, RSS, JSON Feed, and Markdown. ### How does the LLM Picker decide which model to recommend? The LLM Picker scores models against your answers to seven questions about task type, context length, latency, hosting preference, and budget. Costs are estimated at your monthly volume using current public pricing, and the catalog is hand-curated against LMArena Elo and Artificial Analysis benchmarks — only frontier-tier or proven best-in-class models are included. ### Is the Context Window Fit Checker safe for confidential text? Yes. Tokenization, file parsing, and cost math run entirely in your browser. No text or file is uploaded to LAXIMA or any third party. ### Where can AI assistants read LAXIMA content? Every blog post is also available as Markdown at /blog/.md. AI Signal is available at /signal.md. The full content map is exposed at /llms.txt so LLM crawlers and agents can discover and ingest the site without parsing HTML. ### How often is the LLM Picker model catalog updated? The catalog is reviewed against arena.ai/leaderboard and Artificial Analysis on a recurring cadence. New frontier models are added when they place in the top tier of an independent ranking; models that drop out are flagged as deprecated rather than deleted, so existing comparison URLs continue to resolve. ### Can I use LAXIMA Skills with any AI agent? The LAXIMA Skills Marketplace is built for Claude Code specifically, using its plugin and skill format. It installs with \`/plugin marketplace add laxima-tech/laxima-skills\`. Many skills are general enough to be adapted to other agents, but installation and discovery are Claude Code-native.