16,832 skills sorted by stars.
Helps with Morphir Go development including workspace setup, go.work management, branch/worktree handling, TDD/BDD workflow, and p...
Generate production-quality Python code for robot motion planning algorithms that run inPyodide (browser). Creates educational cod...
Use when animation causes dizziness, nausea, disorientation, or vestibular discomfort
Provide inspiring coding wisdom, productivity tips, and encouragement to keep developers motivated and focused
Human-like mouse movement patterns. Use when automating browser interactions to avoid bot detection.
Standardize how a single CLI command is executed in a repo: working dir, argv, timeout, env overrides – and capture exit code, log...
Given an API description and a docs bundle (e.g. from skill.context7_docs), generate a MOVA skill skeleton for a connector: ds/env...
Normalize a single DPP passport input into lab_battery_passport_extended_v1 (happy-path).
Summarizes branch readiness versus a base branch and produces artifacts for PR prep.
Wrapper for skills/mova_check_basic
Helps IDE agents navigate and operate the MOVA Skills Lab: read the registry, plan skill runs and manage episodes.
Minimal example skill that turns a natural-language procedure description into a structured list of steps. Serves as the reference...
Given a repo snapshot and a goal description, produce a structured, step-by-step plan of code changes: which files to touch, in wh...
Given a MOVA skill id, target runtime, and a list of envelopes to implement, generate code skeleton(s) and optional binding JSON f...
Generate a basic cleanup plan (keep/delete/archive/ask) from a filesystem snapshot; no filesystem changes. Input: env.file_cleanup...
Scans a filesystem target and produces ds.file_cleanup_snapshot_v1 (no deletions). Input: env.file_cleanup_snapshot_request_v1.
Runs Skill Seeker for env.skill_ingest_run_request_v1 and returns ds.skill_ingest_run_result_v1.
Persists ds.episode_skill_ingest_run_v1 in the lab’s genetic file store.
LLM-only skill that takes a textual description of a new skill and generates a complete minimal file plan for a new MOVA skill (sc...
Coordinates repo snapshot, gate runs, and optional WF cycle operations for a single station execution.
Deterministically compare two wf_cycle v1.1 runs (IDE vs CLI): compute metrics, compute score, pick winner, and write a compare fo...
Bootstrap a wf_cycle experiment scaffold (rules, inputs, attempts) with A/B/C templates in one deterministic run.
Assemble a canonical wf_cycle winner_pack from compare artifacts (deterministic copy, replay check).
Develop custom MQL5 indicators with proper patterns. Use when creating indicators, debugging OnCalculate(), working with buffers,...
Compile MQL5 indicators via CLI using X: drive mapping to bypass 'Program Files' path spaces issue. Use when compiling MQL5, MetaE...
Generate comprehensive MR/PR descriptions based on branch changes. Use when creating merge requests or pull requests.
Generates intelligent GitLab merge request descriptions from git commits with automatic categorization and Jira integration
Tracks and monitors GitLab merge request activity including comments, status, and real-time updates
ALWAYS invoke this skill BEFORE writing or modifying ANY Rust code (.rs files) even for simple Hello World programs. Enforces Micr...
This skill should be used when designing agent coordination, implementing context handoffs, reducing context overhead, creating mu...
Master QMIX, MADDPG, CTDE - multi-agent learning with coordination and credit assignment
マルチエージェントシステム設計を専門とするスキル。複数のエージェント間の効果的な協調、ハンドオフプロトコルの設計、情報受け渡しメカニズムにより、スケーラブルで保守性の高い分散システムを構築する。Anchors:• Building Microservices...
Consult external AIs (Gemini 2.5 Pro, OpenAI Codex, fresh Claude) for second opinions when stuck on bugs or making architectural d...
Use when stuck on complex problems, need architecture validation, want code review from multiple perspectives, or debugging hits a...
Use Gemini to find existing solutions before building from scratch. Leverages Google Search grounding to discover code examples, l...
マルチモデルコードレビュー。LLMがコードレビューを行った後、GitHub Copilot CLIに精査させて双方の視点を統合した最終レビューを提供。Use when user wants multi-model code review, second opi...