leynos

Diagnose and add "juice" — game feel, feedback, and tactile polish — to games, prototypes, and interactive software. Use this skill whenever the user is building, polishing, prototyping, or reviewing a game (especially action, arcade, platformer, shooter, or rhythm games), or when they ask about game feel, juice, screen shake, hit feedback, particles, easing, tweening, screen pause/hitstop, juicy effects, "making it feel good", or why their prototype feels limp, lifeless, dry, or cheap. Also trigger when reviewing UI prototypes that need tactile response, or when the user mentions Jonasson, Purho, Vlambeer, Nuclear Throne, screen shake, or Steve Swink's "Game Feel" book. Apply even to non-game interactive software when the user wants buttons, transitions, or interactions to feel responsive and satisfying.

Visual strategy, art direction, and design critique for websites. Use this skill whenever the user asks for visual direction, page design strategy, design critique, hierarchy planning, concept exploration, or art direction for any web page or site — including landing pages, service/transactional pages, dashboards, editorial layouts, portfolios, campaign pages, and design-system foundations. Also trigger when the user asks to evaluate an existing web design, generate concept territories, plan visual hierarchy, choose type/colour/image strategy, or review a design for accessibility and communication clarity. This skill produces design rationale, concept directions, hierarchy maps, system strategies, and review notes — not HTML/CSS code. If the user needs implementation, hand off to the frontend-design skill after the design direction is set.

Local-first Ansible testing for roles and modules within collections. Use whenever the user wants to add, run, scaffold, or debug tests for an Ansible collection, role, or module. Triggers include: "test my Ansible role", "add Molecule tests", "run ansible-test", "set up integration tests", "scaffold a test scenario", "run sanity checks", "write unit tests for a module", "test a collection locally". Always prefer this skill over ad hoc shell suggestions when Ansible testing is the subject. The skill covers the full testing stack: Molecule + Podman for roles, ansible-test for modules and collections (sanity, unit, integration). Python 3.12+, collections layout, and Podman are assumed throughout.

Configure and use Biome (biomejs) for TypeScript linting and formatting. Use when setting up Biome in a project, configuring lint rules, migrating from ESLint/Prettier, fixing lint errors, setting up CI pipelines with Biome, or configuring git hooks for code quality. Covers biome.json configuration, file inclusion/exclusion patterns, rule overrides, and integration with build tooling.

Conduct thorough, actionable code reviews that catch real problems without drowning in noise

Generate, modify, or audit `.codescene/code-health-rules.json` files that control CodeScene's code health scan behaviour. Use this skill whenever the user wants to customize CodeScene rule weights, disable specific smells, adjust metric thresholds, scope rules to test vs application code, apply language-specific overrides, or add in-source `@codescene` directives. Also trigger when the user asks why a CodeScene rule is firing, or wants to suppress a smell across a repo or folder subtree.

Write and maintain self-contained ExecPlans (execution plans) that a novice can follow end-to-end; use when planning or implementing non-trivial repo changes.

Using the Firecrawl MCP server to scrape, search, crawl, extract, and browse the web. Use this skill whenever the Firecrawl MCP tools are available and you need to retrieve web content, discover URLs on a site, search the web with full-page content retrieval, extract structured data from pages, perform autonomous multi-source web research, or interact with web pages through a remote browser sandbox. Trigger this skill for any task involving firecrawl_scrape, firecrawl_search, firecrawl_map, firecrawl_crawl, firecrawl_extract, firecrawl_agent, or firecrawl_browser_* tools. Also trigger when the user asks you to "scrape", "crawl", "map a site", "extract data from a page", "search with Firecrawl", or "use the browser sandbox", even if they don't mention Firecrawl by name — provided the MCP tools are connected.

Migrate a Rust codebase to the Polonius borrow checker (location-sensitive analysis, nightly flag -Zpolonius=next) and evolve owned-value internal APIs into the reference-returning, borrow-centric designs that NLL discouraged. Use this skill whenever the user mentions Polonius, NLL limitations, borrow-checker workarounds, defensive clones, double map lookups, get-or-insert helpers, lending iterators, reducing clone counts, or asks to audit, simplify, de-clone, or redesign Rust APIs around borrowing. Also use it when reviewing Rust code containing clone-to-appease-borrowck patterns, entry() calls with cloned keys, id/index indirection standing in for references, or clone-modify-writeback sequences — even if the user does not name Polonius. Provides two modes (workaround retirement; ownership-model evolution), a pattern catalogue with lifetime-versus-aliasing discriminators, an API evolution playbook, worked examples, and a documentation strategy.

Route Rust work to the smallest useful skill. Use for Rust coding, design, compile errors, API questions, crate layout, async, performance, unsafe, or domain-specific Rust work.

Design and maintain Rust unit tests with clear helper boundaries, rstest fixtures and parameterization, serial_test isolation, fallible setup, and rich assertions with googletest, pretty_assertions, and insta. Use when refactoring assertion helpers, replacing brittle boolean assertions, shaping table tests, or deciding between equality, matcher, and snapshot assertions.

Use for Rust crate boundaries, workspace structure, feature flags, public versus internal APIs, layering, and testable module design.

Capture architectural decisions in Rust projects using the Y-Statement format. Use when a choice is hard to reverse, when the rationale will outlive its author, or when reviewers keep asking "why did we pick this?". Especially relevant for typestate, trait bounds, public API shape, `unsafe` invariants, runtime selection, and verification tooling.

Audit and curate a Rust project's dependency graph. Use for `cargo-vet`, `cargo-audit`, `cargo-deny`, lockfile hygiene, version pinning, and the policy of who is trusted to ship what. Also for SemVer guardrails (`cargo-semver-checks`, `cargo-public-api`) at the publishing boundary.

Write and maintain Kani bounded model checking harnesses for Rust. Use when verifying structural invariants, unsafe code, bounded state machines, or dispatch logic via exhaustive symbolic execution.

Write and maintain proptest property tests for Rust, including custom strategies, shrinking discipline, regression files, and state-machine tests. Use when checking that a property holds across a generated input domain and when a unit test or example does not exercise enough of the input space.

Configure and run mutmut v3 for Python mutation testing — fork-based execution, `[tool.mutmut]` in `pyproject.toml`, the `mutmut browse` TUI, `# pragma: no mutate` suppression, and the discipline of promoting surviving mutants to new tests. Use after `python-verification` confirms mutmut is the right adversary.

Run symbolic execution on Python functions with CrossHair to find counter-examples to contracts or assertions, fill coverage holes via `cover`, and detect behavioural drift via `diffbehavior`. Use after `python-verification` confirms CrossHair is the right adversary.

Write and maintain Hypothesis property-based tests for Python, including strategy design, the filtering trap, stateful testing with RuleBasedStateMachine, the example database, and CI tiering. Use after `python-verification` confirms Hypothesis is the right adversary.

Use for Python decorators, descriptors, context managers (function and class form), metaclasses, and multiple dispatch. The common question is "which abstraction hides this complexity at the right level?".

Use for choosing between threads, `asyncio`, `multiprocessing`, and PEP 734 subinterpreters in Python. Covers workload shape (CPU vs I/O), shared state and the GIL, cancellation, and the `concurrent.interpreters` / `InterpreterPoolExecutor` API new in Python 3.14.

Use for choosing a Python data container — `msgspec.Struct`, `dataclasses.dataclass`, `attrs`, `TypedDict`, `NamedTuple`, frozen vs mutable, tagged unions, and the boundary between wire format and domain object.

Use for Python exception design, raising, catching, and logging. Covers narrow `except`, `raise … from …`, domain hierarchies with `Error` suffixes, parameterised logging, `logger.exception`, and the Ruff TRY/BLE/EM/LOG/N818/PERF203 rules.

Use for Python iterators, generators, lazy evaluation, and refactoring deeply nested loops by extracting an iterator or a context manager. Covers `yield`, `yield from`, generator expressions, `itertools` discipline, and async iteration.

Write and revise tutorials and how-to guides — the two practical, action-oriented kinds of documentation. Use this skill whenever the user asks to write, draft, structure, or fix a tutorial, a getting- started guide, a walkthrough, a lesson, a how-to, a task guide, a recipe, a procedure, or a troubleshooting guide. Also trigger when a document tries to both teach and get a job done at once, when a "tutorial" reads like a reference dump, when steps fail for readers, or when the user is unsure whether they need a tutorial or a how-to. The skill first classifies the document by user need (study versus work), then drives a test-the-path workflow: scope the journey or the goal, execute it end to end recording real output, draft to the right anatomy, edit out blurred boundaries, and hand off to reference and explanation. It is grounded in Diátaxis, Carroll's minimalism, Gagné's events of instruction, and cognitive load theory.

Groom and curate a *living* GIST (Goals, Ideas, Steps, Tasks) roadmap as it accretes work during execution — audit findings, code and design review follow-ups, dogfooding fixes, and new ideas. Use this skill whenever you are maintaining an existing roadmap rather than authoring one: when refactoring or re-architecting tasks have piled up and need consolidating into proper steps; when a hardening or refactoring phase has inflated into many single-task "steps"; when new feature ideas risk being buried among refactoring work, or refactoring work risks being dismissed as low value; when deciding what is genuine debt versus self-generating audit churn; or whenever a roadmap has grown and needs to be made legible again. This is the maintenance counterpart to the roadmap-doc skill, which authors a roadmap from design documents — read roadmap-doc for the GIST grammar, format, and anti-patterns this skill assumes.

Write and maintain a project's `CHANGELOG.md` following the Common Changelog style. Use this skill whenever the user asks to create, draft, update, rewrite, or review a changelog; add a release entry; record notable changes since the last tag; cut a release; promote a prerelease; or document a yanked release. Trigger on phrases such as "update the changelog", "add a changelog entry", "what changed since v1.2.0?", "draft release notes from git history", or "write CHANGELOG.md".

Create GitHub pull requests (PRs) with complete draft PR metadata, reviewer-focused descriptions, roadmap and issue references, execplan identification, and en-GB Oxford English. Use whenever Codex opens, drafts, revises, or prepares a pull request description or title for a branch.

Generate terms of reference documents that capture the problem space — domain, market, users, job-to-be-done, scope, constraints, and open questions — before any solution work begins. Use this skill whenever the user asks to write, draft, or produce a terms of reference, project charter, product brief, problem statement, vision and scope document, domain knowledge document, or "what is this for" document. Also trigger when the user starts a new project without an established brief, wants to capture domain knowledge from a subject-matter expert, needs to draw explicit scope boundaries before technical design, or asks to elicit and document the rationale for a system. The skill drives an elicitation-led workflow: prior-art discovery, gap analysis, structured interview, drafting, editing, and handoff to the design and roadmap skills. It produces documents in the style of df12 Productions — precise, evidence-grounded, and free of aspirational fluff.

Generate development roadmaps from design documents, RFCs, and ADRs found in a repository or provided with the prompt. Use this skill whenever the user asks to create, draft, write, or generate a roadmap, execution plan, delivery plan, or development plan for a software project — especially when design documents, RFCs, or ADRs are available as source material. Also trigger when the user asks to turn a design document or set of RFCs into actionable work items, or to plan the build order for a system described in technical documentation. Trigger even for partial requests such as "plan the next phase" or "break this design into tasks" when design documentation is present.

Generate rigorous technical design documents from a problem statement or product brief. Use this skill whenever the user asks to produce a system design, technical specification, architecture document, design document, or product design — whether from scratch, from an existing brief, or by expanding a rough concept into a full specification. Also trigger when the user asks to "write a design doc", "spec this out", "produce an architecture document", "design this system", or provides a problem statement and expects a structured technical output. The skill drives a multi-phase workflow: research, outline, planning, drafting with external artefacts, Mermaid diagram validation, and a mandatory editing pass. It produces documents in the style of df12 Productions design documents — precise, evidence-grounded, and free of fluff.

Write and apply Git commit messages. Use this skill whenever committing code, staging a commit, writing a commit message, or when the user says "commit", "git commit", "save my changes", or asks to describe what changed. Also trigger when reviewing staged changes before committing. This skill enforces file-based commit messages — never pass messages via `-m`.

Package completed visual storytelling video outputs into OpenShot editor projects with the system-installed media-project command. Use when an agent needs to run or verify a playable .osp handoff, preserve production sidecar metadata, or decide whether a project is ready for OpenShot packaging.

Per-shot production specification workflow: takes a completed scene inventory (from scene-inventory-extractor-v2) and decomposes every scene into numbered shots with full directorial direction — actor position and movement, camera mount and motion, lens, lighting setup, practical effects, timing, and clip boundaries. Generates storyboard keyframe images via nanobanana, assembles video generation prompts with model routing, and maintains an asset pipeline with consistent file naming and a generation manifest. Use when a scene inventory exists and the workflow must move from scene descriptions to individual, generation-ready clips. Also trigger when the user mentions "shot list", "shot breakdown", "storyboard", "video prompt", "model routing", "clip generation", or "per-shot direction".

Execute production video generation from shot-specifier outputs through the Higgsfield Model Context Protocol (MCP). Use when prompts, storyboard frames, media roles, model routing, Higgsfield MCP uploads, generate_video calls, status polling, retakes, resume behaviour, or final assembly order are needed. Bridges structured [TAG] prompt files to model-native plain text prompts, validates model duration/aspect constraints, decomposes key-frame shots into supported start/end image clips, tracks uploaded media and job IDs, and writes generation logs.

Deep operating guidance for Kling 3.0 video generation. Use when selecting Kling 3.0 for a shot, designing multi-shot scene structure, writing Kling-native cinematic prompts, planning Elements or Motion Control references, using start/end frame anchors, handling native audio or dialogue, building product/commercial shots, choosing duration/aspect/quality settings, troubleshooting artifacts, or comparing Kling 3.0 against Seedance 2.0, Veo, Sora, DoP/Cinema, or other Higgsfield video routes. Complements shot-specifier and video-generator by turning Kling 3.0's scene-based model behaviour into practical production rules.

Craft high-precision prompts and edit instructions for Nano Banana image workflows, especially when using the local nanobanana MCP tools for generation, editing, character consistency, or multi-image fusion. Use when the task needs structured prompts, reference-role assignment, layout-heavy image specs, typography-heavy images, iterative edit-first refinement, or reliable model/aspect/output-path choices.

End-to-end production-prep workflow: extracts comprehensive scene inventories from narrative writing, extracts continuity inventory and reset-critical state before prompt writing, generates all reference images (characters, locations under multiple angles/conditions, props), produces start/end/keyframe shot references with consistency verification, and then hands off to shot-specifier for per-shot direction, model routing, and prompt manifests. Use when analysing stories, scripts, or prose to create production-ready scene breakdowns with full visual asset pipelines. Also trigger when the user mentions "scene breakdown", "shot list", "character bible", "location bible", "continuity inventory", "reference images", "storyboarding", or any request to prepare narrative material for AI video generation. This skill expects access to an image-generation MCP and vision capabilities.

Deep operating guidance for Seedance 2.0 video generation. Use when selecting Seedance 2.0 for a shot, designing multimodal references, writing Seedance-native prompts, choosing duration/aspect/quality settings, planning batch generations, troubleshooting drift or artifacts, or comparing Seedance 2.0 against Kling, Veo, Sora, DoP/Cinema, or other Higgsfield video routes. Complements shot-specifier and video-generator by turning Seedance 2.0's multimodal model behaviour into practical shot-planning and generation rules.

Build pronunciation tables, generate text-to-speech (TTS) preview samples, and produce phoneticized scripts ready for narration. Use whenever a script is intended for text-to-speech rendering and the user wants to catch words the engine will mispronounce — proper nouns, Gaelic and Welsh names, brand names with idiosyncratic pronunciation (df12, Nginx), model names with embedded numerics (Atari 2600, ESP32), terms of art and acronyms (SaaS, OAuth, JWT), and document specifiers (ADR-0012, RFC 2119). Trigger on phrases like "phoneticize this script", "phonetecize this", "phonetize", "prep this for TTS", "build a pronunciation table", or any task involving text-to-speech narration where pronunciation consistency matters across takes. Drives a phased workflow: detect candidates, suggest phonetic respellings, render preview samples via the Higgsfield MCP TTS tool with Eleven v3, iterate with the user, and emit a final phoneticized script.

Install and operate a full GitHub issue-to-merge workflow in Axinite using event-driven and cron routines. Use when setting up or tuning autonomous project orchestration: issue intake, planning, maintainer feedback handling, branch/PR execution, CI/comment follow-up, batched staging review every 8 hours, and memory updates from merge outcomes.

Build, run, and test Axinite locally using Docker containers and Chrome MCP browser automation.

Pre-merge review checklist based on recurring AI reviewer feedback patterns

Test the Axinite web UI using the Claude for Chrome browser extension.

Best practices for fixing Whitaker Dylint suite findings — per-lint remediation playbook, exclusion policy, and the interaction traps discovered during the leynos estate rollout

Write a complete novel under a Ralph Loop harness. Use this skill whenever the user asks to draft, plan, outline, or write a novel, novella, or any book-length work of fiction (~40k words and up). Also trigger when the user mentions "Ralph Loop" together with prose, fiction, or storytelling; or when the user provides a premise and expects the agent to take it through treatment, character work, conflict analysis, world-building, Save the Cat beat planning, chapter outlining, scene and beat decomposition, drafting, desloppification, and structured critical revision. This skill is the authoritative entry point for long-form fiction generation; prefer it over ad-hoc drafting even when the user asks casually ("just write me a novel about X"). The skill assumes a harness re-enters the agent until the work truthfully reports done, so every operation is idempotent, resumable, and state-driven.

Use the current `mapsplice` CLI to make structural edits to roadmap-shaped Markdown files. Trigger when an agent needs to append, insert, delete, or replace numbered roadmap phases, steps, tasks, or addendum sub-tasks while preserving renumbering and `Requires` references. This skill covers only the functionality available now; it is not a roadmap-grooming, roadmap-authoring, validation, JSON-output, link-checking, or ExecPlan-renumbering skill.

Use this skill whenever the user wants semantic code intelligence through the Weaver CLI, especially for fetching definitions, fetching symbol cards, checking capability support, inspecting daemon state, or performing language-aware renames. Trigger even when the user does not mention Weaver by name if they want IDE-like code navigation or semantic refactors from the terminal.

Use vidai-mock as a local LLM inference simulator for developing and testing software that targets OpenAI-, Anthropic-, and compatible chat APIs. Covers startup, provider/template configuration, streaming physics, tool-call simulation, chaos testing, and observability-driven validation.

Use when running Rust tests with cargo-nextest. Keywords: cargo nextest, nextest, test runner, run tests, test parallelism, test threads, flaky test, retry, slow test, timeout, test group, filterset, test partition, sharding, continuous integration (CI) testing, nextest profile, nextest config, .config/nextest.toml, cargo nextest run, cargo nextest list, test archive, JUnit, stress test, miri, test coverage, cargo-mutants, criterion, debugger, tracer