tekhne

Generates production-ready GitHub Actions workflows, custom actions, and CI/CD configurations following security and performance standards. Creates CI/CD pipelines, test workflows, deployment configurations, matrix builds, caching strategies, composite actions, Docker actions, JavaScript actions, and reusable workflows. Use when creating or scaffolding GHA resources, writing .github/workflows YAML files, setting up build automation, implementing deployment pipelines, adding security scanning, or building reusable actions — including triggers like 'create a workflow', 'build a pipeline', 'add CI', 'set up GHA', or 'generate a YAML workflow'.

Comprehensive toolkit for validating, linting, and testing GitHub Actions workflow files, custom local actions, and public actions. Use this skill when working with GitHub Actions YAML files (.github/workflows/*.yml), validating workflow syntax, testing workflow execution with act, or debugging workflow issues.

Query and display available GitHub Copilot AI models with their capabilities, context limits, and features. Use when: "what models are available", "show copilot models", "list github models", "check model capabilities", "switch models". Examples: - user: "What models can I use with GitHub Copilot?" → fetch and display available models - user: "Show me models with vision support" → filter models by capability - user: "Which model has the largest context window?" → compare model specifications - user: "List all GPT-5 models" → filter by model family

Fetches and analyzes GitLab merge request (MR) comments, metadata, and review feedback using authenticated API calls. Capabilities include fetching comment threads, retrieving reviewer feedback, filtering unresolved discussions, and generating MR activity reports. Use when the user asks about GitLab MR comments, code review discussions, review feedback, approval status, troubleshooting review delays, or needs to fetch merge request metadata via the GitLab API.

Fetches and analyzes GitLab merge request (MR) comments, metadata, and review feedback using authenticated API calls. Capabilities include fetching comment threads, retrieving reviewer feedback, filtering unresolved discussions, and generating MR activity reports. Use when the user asks about GitLab MR comments, code review discussions, review feedback, approval status, troubleshooting review delays, or needs to fetch merge request metadata via the GitLab API.

Creates .gitlab-ci.yml files, configures pipeline stages, defines CI jobs and runners, sets up deployment workflows, and generates reusable GitLab CI/CD templates following current best practices and security standards. Use when users ask to create or build a GitLab CI/CD pipeline, CI config, build pipeline, deploy pipeline, GitLab YAML, CI jobs, or any .gitlab-ci.yml configuration from scratch or for a new project.

Validates .gitlab-ci.yml syntax, detects security misconfigurations in job definitions, checks for deprecated keywords, ensures proper stage ordering, and audits pipeline configurations for best practices. Use when working with .gitlab-ci.yml files, validating GitLab CI/CD pipeline syntax, debugging configuration errors, checking for hardcoded secrets or credentials in pipeline jobs, optimizing pipeline performance with DAG or cache, or performing security audits on GitLab CI/CD configurations.

Record a session goal as a dated file with items plus evidence, keep its status current, then answer "what's left" in under 100 words: achieved, parked, still open. Use when the user states a session goal, asks what's left, what's outstanding, what's still open, whether the goal is met, are we done, where the session got to. Also use to park an item, to promote an overgrown goal into a plan, to close a goal out.

Search Google Scholar for academic papers and author profiles. Use when discovering papers to triage — by keyword, author, or year range. Returns titles, authors, abstracts, and links. Triggers: search papers, find papers, google scholar, search scholar, find author, author profile, literature search, paper discovery, search academic literature.

Search Google Scholar for academic papers and author profiles. Use when discovering papers to triage — by keyword, author, or year range. Returns titles, authors, abstracts, and links. Triggers: search papers, find papers, google scholar, search scholar, find author, author profile, literature search, paper discovery, search academic literature.

Conduct a structured, one-question-at-a-time interview to explore a specific topic or decision — each question offers 3-4 concrete, mutually exclusive options plus a free-text path, and later questions adapt to prior answers rather than following a fixed script. Ends with a recap the user confirms before finalizing, and only then produces a synthesized answer or (when the interview clearly feeds downstream work) a written brief. NOT for open-ended ambiguity-surfacing (use socratic-method) or single-fact lookups.

Comprehensive toolkit for generating best practice Helm charts and resources following current standards and conventions. Use this skill when creating new Helm charts, implementing Helm templates, scaffolding Chart.yaml and values.yaml, defining deployment templates, service definitions, ingress configurations, .tpl helpers, or building Helm projects from scratch. Trigger phrases include "create", "generate", "build", "scaffold" alongside terms like "kubernetes helm", "k8s charts", "helm package", "chart dependencies", "values.yaml", or "helm install".

Comprehensive toolkit for validating, linting, testing, and analyzing Helm charts and their rendered Kubernetes resources. Use this skill when working with Helm charts, validating templates, debugging chart issues, working with Custom Resource Definitions (CRDs) that require documentation lookup, or checking Helm best practices.

Use for "how does X work", code walkthroughs before changing something, and placement / ownership / layering questions ("where should this live", "which package owns this", "is this the right layer"). Explains subsystem architecture, runtime flow, onboarding mental models. Can critique architecture. DO NOT use for design rationale or history (use why instead), or for proving a change is safe to ship (use blast-radius instead). Triggers: how does X work, walk me through X, where should this live, critique this architecture, whats wrong with this design.

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases. Credits: Original skill by @blader - https://github.com/blader/humanizer

Converts a PRD or requirements document into a structured, phased implementation plan with individual phase files and granular per-task files written to .context/plans/. Also restructures existing monolithic planning documents into digestible, hierarchical directory structures. Creates a root plan index summarising all phases, a numbered phase file per phase, and a numbered task file per task inside each phase directory. Use when the user asks to create an implementation plan, break down a PRD, convert requirements to tasks, structure project phases, generate a roadmap, plan a project in sprints, organise task breakdown, split a monolithic planning doc, or decompose a spec into phases and tasks.

Validates, sanitizes, normalizes user inputs before processing. Prevents injection attacks, data corruption, runtime errors in production. Enforces schema-driven validation at entry points with explicit rejection policies for malformed payloads.

Generates Jenkinsfiles with stages, agents, parallel builds, post-build actions, and security scanning for Declarative and Scripted pipeline syntaxes. Use when creating a Jenkins pipeline script, Groovy pipeline, or build configuration; implementing CI/CD workflows, continuous integration, or build automation; adding Docker/Kubernetes deployments, matrix builds, parameterized pipelines, or DevSecOps security scanning to a Jenkins setup.

Comprehensive toolkit for validating, linting, testing, and automating Jenkinsfile pipelines (both Declarative and Scripted). Use this skill when working with Jenkins pipeline files, validating pipeline syntax, checking best practices, debugging pipeline issues, or working with custom plugins.

Ready up Jira tickets for refinement, including brand-new not-yet-keyed backlog items, by gathering context from linked incidents or interviewing the user when no incident exists, populating a YAML template against the project's 'ready for refinement' standard, validating it against a JSON schema plus gap-detection heuristics for testability and vagueness, and generating a structured markdown document. Use when asked to ready up, prepare for refinement, draft a new backlog ticket, or write up a specific ticket key.