kevin-burns
UserA small collection of MIT-licensed Claude Code skills that I build
Categories
Indexed Skills (28)
use-linearis
Use when running Linear.app operations from the command line — creating, updating, archiving, listing, or filtering issues, setting project milestones, or wiring blocked-by relations via the `linearis` CLI (binaries `linear` and `linearis`, JSON output) instead of an MCP or the web UI. Triggers on any Linear issue/project/milestone task in a terminal, and on syncing Kevin's Ogham roadmap with its shared-memory database. Covers generic install/auth setup, the CLI's sharp edges, and the local env.sh split that keeps workspace identifiers out of the repo. Not a full reference — that's `linear <cmd> --help`.
terragrunt-skill
Comprehensive Terragrunt 1.x skill for generating, validating, reviewing, and debugging Terragrunt configurations (root.hcl, terragrunt.hcl, terragrunt.stack.hcl, units, stacks, catalogs) across AWS, Azure, and GCP. Use this skill whenever the user mentions Terragrunt, terragrunt.hcl, root.hcl, stack files, units, HCL orchestration of OpenTofu/Terraform, remote state DRY configuration, run --all, dependency blocks between modules, or asks to scaffold/lint/diagnose multi-environment IaC layouts — even if they don't say "Terragrunt" explicitly but show Terragrunt HCL.
clear-and-human
Construct, review, score, and rewrite written content so it reads like a specific human wrote it, not an AI. Use this skill whenever the user wants to: write or draft prose for humans (docs, README, runbook, ADR, PR/commit message, blog post, LinkedIn post, email, Slack message, or a spoken explainer/tutorial video script); humanize or de-slop AI-generated text; check whether writing "sounds like AI"; review a draft for AI texture; rewrite content in their own voice; score a draft for authenticity or clarity; or tighten and sharpen prose. Also trigger on "humanize", "make it sound human", "sounds like AI", "does this sound like AI", "voice check", "review my draft", "rewrite in my voice", "tighten this up", "edit for clarity", "video script", "explainer script". Auto-detects content type and applies channel-specific rules. Defaults to a neutral, factual voice and never invents specifics to add texture. For deliberately persuasive marketing copy (ads, hooks, LinkedIn/Bluesky growth posts, video titles and thum
markdown-converter
Convert documents and files to Markdown using markitdown. Use when converting PDF, Word (.docx), PowerPoint (.pptx), Excel (.xlsx, .xls), HTML, CSV, JSON, XML, images (with EXIF/OCR), audio (with transcription), ZIP archives, YouTube URLs, Outlook (.msg), or EPubs to Markdown format for LLM processing or text analysis. This is a ONE-OFF conversion of a file or URL you already have. For fetching an external source ONCE and keeping it as a pinned, provenance-stamped artifact that agents re-read instead of re-fetching -- reproducible, offline, versioned -- use source-snapshot instead.
nano-banana-pro-json
Generate and edit images using Google's Nano Banana Pro (Gemini 3 Pro Image) API. Use when the user asks to generate, create, edit, modify, change, alter or update an image, or points at an existing image file and asks to change it ("change the background", "replace X with Y"). Covers logo and brand-identity design ("design a logo", "brand mark", "wordmark", "icon", "brand identity"); product and marketing images ("product shot", "e-commerce photo", "hero image", "lifestyle photo", "ad creative", "packaging mockup"); and illustrated infographics and explanatory graphics ("infographic", "explainer graphic", "comparison graphic"). Style presets (cinematic, film, fashion, studio), aspect ratios (1:1, 4:3, 16:9, 9:16, 3:2, 2:3, 4:5) and WebP output. This is the default skill for generating and editing raster images.
azadvertizer
Deterministic, offline-first lookups over Azure Policy, Policy Initiative, and RBAC Role metadata sourced from AzAdvertizer's CSV exports — including the cross-references that exist nowhere else in one place (which roles a policy uses, which initiatives include a policy, which policies a role is used by). Use whenever you need accurate current facts about an Azure built-in policy, initiative/policy-set, or RBAC role — definitions, effects, allowed effect values, categories, role actions/dataActions, or the policy↔role and policy↔initiative relationships — for writing or reviewing Azure IaC, governance, or landing-zone work. Fetches each CSV once into a provenance-stamped cache and answers queries offline; stdlib only, JSON envelope output. Pairs with terragrunt-skill, azure-architect, and fact-verifier (snapshots become tier-1 sources).
report-builder
Build self-contained, single-page HTML reports and dashboards from data using Python + Jinja2 + Bootstrap 5 with Chart.js or Plotly. Use whenever the task is to produce an HTML report, data dashboard, metrics page, status page, or any single-file web artifact rendered from data — even if the user only says "report", "dashboard", "summary page", "visualize this", or hands you a CSV/DataFrame/JSON and wants it shown. Covers the render harness (Jinja2 autoescape discipline, passing data to JS safely with tojson), the Chart.js-vs-Plotly decision, Bootstrap 5 layout, and producing a portable single file. Pairs with markdown-converter (to ingest source docs) and is read by code-builder when it implements front-end report work.
social-image-prep
Resize and format images for social media platforms. Use when the user needs to prepare an image for LinkedIn, Bluesky, Reddit, Hacker News, or other social platforms. Triggers on "resize for linkedin", "image for social", "prepare image for posting", "social media image", "resize for bluesky", or any request to optimize an image for a specific social platform.
terraform-registry
Provider-agnostic CLI for targeted search and inspection of the Terraform Registry via its JSON API — any provider (AWS, GCP/google, Azure/azurerm, GitLab, OpenStack, Kubernetes, ...). Use to find modules by keyword, inspect a module's inputs/outputs/versions, or look up a resource type's attributes, WITHOUT web-scraping or dumping pages into context — it fetches the JSON payload, strips it locally, and returns only what you asked for. Caches every payload as a provenance-stamped snapshot so repeat calls are offline and token-free. Use whenever you need accurate, current Terraform module/provider facts for writing or reviewing IaC.
ux-audit
Heuristic usability and accessibility audit of existing web pages — load a rendered page, evaluate it against Nielsen's 10 usability heuristics + WCAG 2.2 (A/AA) + responsive behavior + the page's own goal, and return prioritized findings with a concrete fix for each. Use whenever the task is to review, audit, critique, or "find usability/UX problems" on one or more web pages, do an accessibility (a11y) check, assess responsiveness, or propose usability fixes — even if the user just says "is this page any good", "what's wrong with this UI", "make this more usable", or hands you a URL/screenshot. This is a review/audit method, not a design-decision debate (that's design-council) and not functional testing (that's webapp-testing). Read by the ux-auditor agent, which renders each page with a browser driver and fans out one auditor per page.
c7search
Retrieve up-to-date documentation and code examples for any software library, framework, or API via the Context7 service, using the `c7search` CLI. Use this skill whenever looking up how to use a library or framework, finding current code examples for a specific API or feature, verifying the correct signature or usage of a library function, or checking library behavior that may have changed since the training cutoff — even when the user doesn't name Context7 or c7search explicitly. `c7search` is a single Go binary wrapping Context7's public v2 API with on-disk caching, retries, and predictable exit codes.
dev-fleet
Orchestration playbook for driving the development agent fleet (code-builder, fact-verifier, coherence-checker, code-reviewer) through a build → verify → cohere → review → commit pipeline with explicit, deterministic hand-offs. Use when implementing a non-trivial change where correctness and fact-accuracy matter and you want the steps to actually run in order rather than hoping the orchestrator delegates. Also use when deciding which fleet agent to dispatch for a task, or when wiring a new agent into the pipeline. Covers how to pass context between agents, the fact-gate and coherence-gate before commit, the loop-back semantics on each gate, and handing off to commit-pr.
hook-and-human
Write, punch up, and review marketing copy that stops the scroll and converts, while still sounding like a real person. Use this skill whenever the user wants to: write a LinkedIn post, X/Twitter post, Bluesky post, cold or marketing email, ad, landing-page section, headline, hook, lead magnet, or YouTube packaging (video title, thumbnail text, description hook, end-screen/CTA, community post); "punch up" or "make this convert" or "make this land"; sharpen a CTA; or review copy for stopping power and conversion. Also trigger on "hook", "scroll-stopper", "make it punchy", "marketing copy", "sales copy", "cold email", "ad copy", "landing page copy", "lead magnet", "bluesky", "youtube title", "video title", "thumbnail", "make this convert". Deploys persuasion patterns (hooks, frameworks, one strong CTA) on purpose, reads WRITING_CONTEXT.md for voice and approved facts, and never fabricates specifics. For neutral, credibility-first writing (docs, README, plain explanation, or a teaching/explainer video script) us
frontier-rounds
Interview the user in breadth-first rounds until a design is settled, asking every question whose prerequisites are already answered in one batch rather than one at a time. Use when a plan, design, spec or decision needs stress-testing before work starts; when the user says "grill me", "stress-test this", "poke holes in this", "what am I missing", "interrogate this plan", "ask me what you need to know"; or when another skill needs a structured elicitation pass. Produces settled decisions, not deliverables. For open-ended idea generation use superpowers:brainstorming instead — this is for a design that already exists and needs pinning down.
transcribe-summarize
Transcribe audio locally on macOS, Windows or Linux, and optionally write it up as meeting notes. Use whenever the user has an audio or video file and wants what was said - "transcribe this", "what was said on the call", "turn this recording into notes", "write up this meeting", "subtitle this", "get me an .srt", a voice memo, a dictation, an interview, a lecture, a podcast. Runs on-device by default with Whisper (mlx-whisper on Apple Silicon, faster-whisper everywhere else, Parakeet when asked for); Groq, OpenAI and ElevenLabs Scribe are available but only when named explicitly, and never without first stating what will be sent and what it will cost. Normalises and silence-trims the audio with ffmpeg before decoding, which measurably beats reaching for a bigger model, and filters the fabricated segments Whisper invents over silence. Also produces a factual meeting-notes document and a PDF. Not for writing prose or summarising text you already have.
convert-to-webp
Convert images (PNG, JPG, etc.) to WebP format. Use when saving screenshots or images for web projects, Hugo sites, or any context where WebP is preferred.
cv-and-human
Tailor and polish a CV/resume - or a LinkedIn profile - to maximise its score in applicant tracking systems (ATS) and LinkedIn recruiter search, for both JD-matching and JD-less screeners. Use this whenever the user wants to optimise, tailor, rewrite, or "ATS-proof" a CV or resume, asks why their resume isn't getting past automated screening, wants a keyword/gap analysis against a job description, wants to remove AI-generated texture from / de-slop / humanize a CV or LinkedIn profile, or wants to check whether a CV parses cleanly. ALSO use for the LinkedIn PROFILE as a career document: "optimise my LinkedIn profile", "rewrite my LinkedIn headline", "my LinkedIn About section", "the experience bullets on my LinkedIn profile", "why am I not showing up in recruiter searches", "make my LinkedIn match my CV", "personal brand positioning". Trigger even with no job description, as long as the user names something to be DONE to the document - tailored, ATS-proofed, parse-checked, de-slopped. Do NOT use when the user
cv-evidence-base
Interrogates a CV or resume to recover the evidence that never made it onto the page, and works out which roles the person is genuinely credible for. Grades their background against role archetypes derived from what they actually did rather than from their job titles - including archetypes they are NOT credible for - asks the oblique questions that dislodge buried achievements, names where the page would get binned in a seven-second scan, and maintains an evidence base plus an action ledger across sessions. Use this whenever the user has NO target role in mind and is asking an open question about themselves: what roles they could realistically go for, whether they are pitching themselves right, whether they are pigeonholed, why they get no callbacks or interviews, what they are missing, or what their CV says about them. Use it when they hand over a CV with no clear instruction - "does this look OK", "be honest with me", "am I positioned right". ALSO use for a career change, a step up, going freelance or contr
excalidraw-diagram
Create Excalidraw diagram JSON files that make visual arguments. Use when the user wants to visualize workflows, architectures, or concepts.
job-feeds
Aggregate sanctioned public job feeds into one deduplicated local database, match postings against the user's career lanes, and render a filterable self-contained HTML report. Use whenever the user wants to search or monitor job boards - "find me remote platform engineering roles", "what jobs came up this week", "check the job boards", "aggregate job listings", "what's new since I last looked" - or wants a report of current openings across multiple sites. Covers nine documented JSON APIs and RSS feeds from eight publishers (Arbeitnow, Jobicy, Remotive, Remote OK, Working Nomads, 4 Day Week, We Work Remotely, Python.org Jobs), weighted towards the German and EU-remote market. NOT for LinkedIn - that needs a signed-in session and is a separate tool. This skill never scrapes HTML, never works around a block, and never republishes what it collects.
travel-planning
Turn a trip request into a structured, editable travel plan — a day-by-day itinerary plus a reconciled budget — as a Markdown document. Use this whenever the user wants to plan a trip, vacation, or holiday: "help me plan a week in Portugal", "build an itinerary for 5 days in Tokyo with my kids", "map out a road trip", "we have $3k for a long weekend, what can we do", "organize my Japan trip", or any request to structure travel across days and a budget — even if they don't say the word "itinerary". This is a reasoning-and-structuring skill: it plans, paces, and budgets, and will do a best-effort web lookup to anchor cost estimates in typical or seasonal prices (labeled, sourced, not live quotes). It does NOT make bookings, transact, or read real-time seat/room inventory — steer those to the actual booking sites and keep planning.
cv-cover-letter
Draft a cover letter from a job posting and the applicant's own CV and evidence base, making only claims that trace to something they actually said, and stopping when the evidence stops rather than filling a word count. Use when the user asks for a cover letter, a covering letter, a letter of application, a motivation letter or an Anschreiben; when they want an existing draft checked for claims it cannot support; or when they ask whether a posting is worth applying to before writing one. Runs on any posting — a URL, a pasted advert, an email — not only LinkedIn. Do NOT use for the CV itself (cv-and-human) or for recovering what someone has done in the first place (cv-evidence-base).
readability
Check whether a draft is actually readable by locating where a reader falls off — weak paragraph junctions, back-references with no antecedent nearby, and terms used before they are explained — then dispatch a fresh-context second reader to catch contradictions and repetition that no script can see. Use this whenever the user asks whether something is readable, clear, hard to follow, confusing, well-structured or "does this flow"; whenever they ask for a readability check, a readability score, a Flesch or grade-level reading, or a second opinion on a draft; and as the last review pass before publishing a blog post, README, ADR, runbook or long technical explanation. Also trigger on "read this end to end", "does this make sense", "fresh eyes on this", "where does this lose people", "is this too dense", "second reader", "cohesion", "flow check". Reports locations and never a grade level — if the user explicitly wants a Flesch or Gunning Fog number, use this skill and explain why it is not computed. For AI textu
trilium-capture
Write findings, clipped material and long-form documents into a self-hosted Trilium Notes instance over its native MCP — filed under a project, labelled with a controlled vocabulary, and revised in place rather than duplicated. Use when the user says to store, capture, save or file something in Trilium; when a research finding or an article should outlive the session; or when a document produced with the user (a plan, a draft, a report) should live in their notes instead of on one machine. Do NOT use for short recallable facts an agent needs mid-task — those belong in Ogham shared memory.
business-plan
Build a realistic, investor-credible business plan from a founder's idea — full narrative plan, a one-page summary, and a ~300-word investor pitch — as an editable Markdown document. Use this whenever the user wants to plan, pitch, or pressure-test a venture: "write a business plan for my [idea]", "is my startup idea worth building", "build my go-to-market", "size this market", "do a competitor teardown", "make me an investor one-pager", "3-year financials for my SaaS", "should I raise for this". This skill's defining feature is honesty: it researches-and-cites market/competitor facts, computes financials from YOUR assumptions, marks anything unknown as a validate-this placeholder, and never invents a market size, a competitor's pricing, or a revenue number. It ends every plan with a straight go / no-go / reshape verdict, not cheerleading.
writing-for-agents
Writing documents for agents. Use when creating or editing skills, or modifying AGENTS.md or CLAUDE.md.
beads
Use when working in a repository that uses bd or Beads for durable project task tracking, issue dependencies, blocker management, multi-session handoff, or shared work memory. Trigger when the user asks to find ready work, claim or close tasks, create follow-up work, inspect blockers, recover project context, or choose between local planning and persistent project tracking.
transcribe-summarize
Transcribe audio locally on macOS, Windows or Linux, and optionally write it up as meeting notes. Use whenever the user has an audio or video file and wants what was said - "transcribe this", "what was said on the call", "turn this recording into notes", "write up this meeting", "subtitle this", "get me an .srt", a voice memo, a dictation, an interview, a lecture, a podcast. Runs on-device by default with Whisper (mlx-whisper on Apple Silicon, faster-whisper everywhere else, Parakeet when asked for); Groq, OpenAI and ElevenLabs Scribe are available but only when named explicitly, and never without first stating what will be sent and what it will cost. Normalises and silence-trims the audio with ffmpeg before decoding, which measurably beats reaching for a bigger model, and filters the fabricated segments Whisper invents over silence. Also produces a factual meeting-notes document and a PDF. Not for writing prose or summarising text you already have.
Bio shown is the top-scored skill's repo description as a fallback — real GitHub bios land in a future update.