Explorar skills

Build resumable state-machine workflows with checkpoint patterns, progress preservation, and automatic recovery for complex multi-phase operations that need to survive interruptions, timeouts, and failures.

Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always

Complete brand development system with emotive foundation. Triggers on requests for brand identity, logos, visual systems, or design guidelines. Creates distinctive, anti-AI-slop design from strategy through delivery.

JIRA Service Management via the jira-as wrapper: service desks, request types, requests, customers, organizations, queues, SLAs, approvals (8 sub-domains). Triggers: 'create JSM request', 'list service desks', 'SLA status for KEY', 'approve request KEY', 'list queue NAME'. Requires JSM-licensed tenant + agent role. NOT for core Jira issue ops (mk:jira-issue); NOT for project admin (mk:jira-admin).

SOLID principles for Rust 2024+. Files < 100 lines, traits separated, modular architecture. Modules MANDATORY.

Pack an EXTERNAL repository into a single AI-friendly file (markdown/xml/json). Use for third-party library analysis, security audits, or handoff to external LLMs. Do NOT use to pack the current project for inbound context — the host runtime already reads files lazily. Triggers: 'pack this repo', 'snapshot of X', 'export codebase', 'repomix'.

Systematic documentation audit and maintenance. This skill should be used when documentation may be stale, missing, or misorganized — after feature work, refactors, dependency upgrades, or as a periodic health check. It prescribes folder structure for docs/ and manual/, dispatches haiku subagents for codebase/doc scanning, and routes doc creation to specialized agents (reference-builder, technical

User-invoked structural review for subtle AI tells in prose artifacts — rhythm patterns, rhetorical reflexes, hedging cadence, performative emphasis, and the structural shapes that mark text as machine-generated even after surface tells are cleaned up. Produces a findings report citing each tell by line with a fix-direction, then offers a rewrite pass. Use on artifacts that matter: public READMEs,

Ticket/PRD intake: product area classification, completeness scoring, RCA, technical assessment. Works with Jira (via mk:jira-issue / jira-as), Linear (via MCP), GitHub (via gh CLI), or manual paste. Triggers: 'analyze ticket', 'intake PRD', 'triage issue', 'classify ticket', 'check ticket'.

This skill should be used when working with reinforcement learning tasks including high-performance RL training, custom environment development, vectorized parallel simulation, multi-agent systems, or integration with existing RL environments (Gymnasium, PettingZoo, Atari, Procgen, etc.). Use this skill for implementing PPO training, creating PufferEnv environments, optimizing RL performance, or d

Enforce direct, concise prose style and catch writing slop. Use when writing or editing PR descriptions, issue bodies, commit messages, documentation, Slack messages, or any human-facing text. Also use when asked to clean up, rewrite, or "de-AI" existing text.

Test-to-requirement coverage mapping. Reads plan acceptance criteria and test files, produces a coverage gap report showing which requirements have no tests. Use during Phase 2 (Test) or Phase 4 (Review) to verify test completeness. Named after the Nyquist sampling theorem — sufficient test coverage prevents aliased (missed) requirements. NOT for running tests (see mk:testing); NOT for structural