Draft, rewrite, or audit developer documentation using an independently expressed interpretation of the Google developer documentation style. Use for API guides, tutorials, concepts, setup instructions, code explanations, command-line documentation, and technical content for a global developer audience.
Draft, rewrite, or audit plain-language public-service content using an independently expressed interpretation of GOV.UK content design. Use for eligibility pages, government guidance, policy explanations, forms, transactions, public notices, and content that must help people make a decision or complete a service task.
Draft, rewrite, or audit Kubernetes and cloud-native documentation using an independently expressed interpretation of Kubernetes documentation style. Use for concepts, tasks, tutorials, references, configuration, operations, and version-sensitive guidance involving clusters, workloads, APIs, kubectl, or Kubernetes…
Draft, rewrite, or audit friendly customer and product communication using an independently expressed reference-only interpretation of Mailchimp's content guidance. Use for customer education, product copy, campaign guidance, onboarding, help messages, newsletters, and brand content that should be plainspoken…
Draft, rewrite, or audit web-platform documentation using an independently expressed interpretation of MDN Web Docs writing guidance. Use for HTML, CSS, JavaScript, Web API references, browser-facing concepts, tutorials, learning material, compatibility notes, and examples for web developers at a stated experience…
Draft, rewrite, or audit friendly, concise product and technical UX content using an independently expressed reference-only interpretation of Microsoft writing guidance. Use for product help, setup, support, interface text, error messages, and technical content that should feel conversational, scannable, global, and…
Draft, restructure, or audit evidence-led scientific and engineering reports using an independently expressed reference-only interpretation of official NASA technical-publication guidance. Use for test and experiment reports, design descriptions, technical memoranda, engineering analyses, and scientific publications…
Draft, rewrite, or audit patient-facing health and service content using an independently expressed reference-only interpretation of official NHS content guidance. Use for symptoms and conditions pages, appointment messages, treatment explanations, health-service instructions, and digital health journeys that must…
Draft, rewrite, or audit modular enterprise technical documentation using an independently expressed interpretation of the Red Hat supplementary style guide. Use for administration, installation, configuration, security, troubleshooting, procedures, concepts, and references that must be precise, reusable, and…
Draft, rewrite, or audit investor-facing financial and legal disclosure using an independently expressed interpretation of official SEC plain-English guidance. Use for prospectus summaries, risk factors, shareholder letters, offering materials, and securities disclosures that must be easier to understand without…
Draft, restructure, or audit specification-style technical reports using an independently expressed reference-only interpretation of W3C editorial guidance. Use for protocols, standards, interoperability documents, conformance requirements, and technical specifications that must separate normative requirements from…
10 skills that cut your AI bill with proof instead of vibes: cheap/premium routing, advisor call budgets, token receipts audits, tested fallbacks, free-tier batch sizing, guarded cheap swaps, reasoning-effort throttles, evidence-based model bake-offs, context diets, and free-model triage. Every skill carries a…
AGENTS.md instructions for Neeeophytee/ai-cost-cutter-skills, covering cost-cutter guidelines, visibility before optimization, routing, tokens and choosing and keeping models.
Claude Code instructions for Neeeophytee/ai-cost-cutter-skills, covering cost-cutter guidelines, visibility before optimization, routing, tokens and choosing and keeping models.
Enforce a hard cap and a drift-check when a cheap executor model consults an expensive advisor model, and compute the effective cost from actual call counts instead of a benchmark's assumed rate. Use when the user adopts the advisor or orchestrator pattern, pairs a cheap model with an expensive reviewer, or quotes a…
Before swapping any workload to a cheaper model, declare the cases the premium model still dominates and prove they keep routing to premium. Use when the user wants to "just switch" to a cheaper model (text, image, or video), or asks whether a cheap model is good enough to replace an expensive one.
Cut agent token spend by shrinking what enters the context window. Index the repo or corpus once and query it instead of re-reading files on every question. Use when the user complains their coding agent burns tokens, the context fills up fast, the same files get read repeatedly, or the bill scales with conversation…
Route high-volume, low-stakes triage (reading piles, inbox summaries, needs-reply flags) to a free model with a strict output schema. Use when the user wants one-line summaries of many items cheaply, asks to triage email, articles, or reports with AI, or wants to decide what's worth reading without paying premium…
Size a big one-time batch job against a free tier's rate limit and token budget BEFORE starting it, with a proven wall-clock ETA. Use when the user wants to label a dataset, summarize an archive, or process a large backlog for free (or on a tiny rate limit), or asks "will this finish overnight?".
Choose a model with evidence by running the few prompts that actually matter across candidate models inside a free tier's caps, picking by a stated criterion. Use when the user asks "which model should I use", wants to evaluate a newly launched model, or is choosing between models for a specific task.
Stop paying for deep reasoning on easy turns by setting a modest default reasoning effort and escalating per task. Use when the user runs a reasoning model in an agent and the bill is dominated by output or thinking tokens, or asks about reasoningeffort, thinking budgets, or why a cheap model is still expensive to run.
Cut LLM spend by routing bulk work to a cheap model and escalating only the hard turns to a premium one. Use when the user says their AI bill is too high, asks to "use a cheaper model", or wants two-tier model routing without losing quality on the hard tasks.
Pin an open-weights fallback model with a tested-on date and real smoke prompts, so a pulled or deprecated model is a two-minute config swap instead of a lost week. Use when the user worries a model could vanish or be deprecated, builds anything important on one model, or asks about model failover and resilience.