Claude Skills by Neeeophytee

Draft, rewrite, or audit inclusive US digital-government content using an independently expressed interpretation of the 18F Content Guide. Use for public-service websites, forms, applications, transactional messages, help content, notices, and government digital experiences that should help people complete a task with minimal bureaucratic burden.

Draft, rewrite, or audit concise interface text using an independently expressed reference-only interpretation of Apple's Human Interface Guidelines for writing. Use for buttons, labels, settings, alerts, errors, onboarding, notifications, permissions, empty states, and multi-screen app flows where wording must make actions and consequences clear in limited space.

Draft, rewrite, or audit evidence-based public-health communication using an independently expressed interpretation of the CDC Clear Communication Index. Use for patient explanations, health campaigns, risk and emergency messages, public-safety notices, and educational health material that must make one message and the audience's next action unmistakable.

Draft, rewrite, or audit approachable developer product documentation using an independently expressed interpretation of the GitHub Docs style. Use for product workflows, how-to guides, conceptual overviews, troubleshooting, security guidance, and documentation that should move developers from prerequisites to a verified outcome.

Draft, rewrite, or audit concise product and engineering documentation using an independently expressed interpretation of the GitLab documentation style. Use for product guides, configuration, administration, tutorials, troubleshooting, contributor docs, and technical pages that must be searchable, precise, and localization-friendly.

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 resources.

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, empathetic, and lightly playful only when the situation permits.

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 level.

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 action-oriented.

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 that must preserve measurements, conditions, limitations, and traceability from evidence to conclusions.

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 remain clinically accurate, inclusive, accessible, and explicit about next steps.

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 supportable across product versions.

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 losing any material fact, qualification, condition, or uncertainty.

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 explanation and define precise, testable behavior without inventing requirements.

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 benchmark discount like "63% of the price".

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 length.

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 rates for it.

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 reasoning_effort, 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.

Attribute AI usage by tokens AND dollars so a high-volume cheap model is never mistaken for the expensive one. Use when the user asks where their AI spend actually goes, why the bill is high, which model is costing the most, or wants a usage audit across agents and models.