mova-workflow-author-v0
Use for creating new packs/workflows, adding domains/workers, or adding quality/neg suites with station-compatible scripts.
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Use for creating new packs/workflows, adding domains/workers, or adding quality/neg suites with station-compatible scripts.
LLM-only skill that takes a textual description of a new skill and generates a complete minimal file plan for a new MOVA skill (schemas, envelope, manifest, prompt profile, runtime binding, docs, cases).
Summarizes branch readiness versus a base branch and produces artifacts for PR prep.
Given a repo snapshot and a goal description, produce a structured, step-by-step plan of code changes: which files to touch, in what order, with risks and done-criteria. This skill does not modify files and doe...
Given a MOVA skill id, target runtime, and a list of envelopes to implement, generate code skeleton(s) and optional binding JSON files that connect these envelopes to real execution (HTTP, CLI, etc.).
Runs Skill Seeker for env.skill_ingest_run_request_v1 and returns ds.skill_ingest_run_result_v1.
Runs npm validate/test/smoke gates and emits a JSON gate report with log paths.
Generates a static MOVA AI bootstrap pack for a target model/environment (no LLM calls). Input: env.mova_ai_bootstrap_generate_v1, output: ds.mova_ai_bootstrap_pack_v1.
Minimal example skill that turns a natural-language procedure description into a structured list of steps. Serves as the reference pattern for other MOVA skills in this lab.
Helps IDE agents navigate and operate the MOVA Skills Lab: read the registry, plan skill runs and manage episodes.
Wrapper for skills/mova_check_basic
Fetches up-to-date, version-aware library documentation from the Context7 MCP server before working on a project.
Persists ds.episode_skill_ingest_run_v1 in the lab’s genetic file store.
Given an API description and a docs bundle (e.g. from skill.context7_docs), generate a MOVA skill skeleton for a connector: ds/env schemas, manifest, prompt profile, runtime binding stub, cases, and docs.
Bootstrap a wf_cycle experiment scaffold (rules, inputs, attempts) with A/B/C templates in one deterministic run.
Standardize how a single CLI command is executed in a repo: working dir, argv, timeout, env overrides – and capture exit code, logs, and a short human-readable summary.
Use for running station one-button flow (gates -> quality -> finish-branch -> episode store) with evidence paths and zero interactive branches.
LLM-only skill that analyzes a snapshot of a single disk or partition and generates a safe, structured cleanup plan. Identifies obvious junk, heavy folders, and proposes step-by-step actions to reclaim space wi...
Deterministically compare wf_cycle runs as a Proof of Invariance step: compute metrics, score the double-run, and write canonical compare artifacts for the result_core outputs.
Operate macOS desktop UI via the desktop-ops CLI using the snapshot/ref/action workflow. Use when an agent needs to read UI state with `desktop-ops snapshot --json`, select refs, and execute `click`, `set-value...
Use this skill when the user asks about ROS message types, message fields, sensor_msgs, geometry_msgs, std_msgs, nav_msgs, or needs to understand how to work with specific message structures like sensor_msgs/Im...
Use this skill when the user encounters ROS errors, issues, or unexpected behavior. Covers common error messages, diagnostic approaches, and proven solutions for roscore issues, topic problems, build errors, ne...
Use this skill when the user needs help writing, understanding, or modifying ROS launch files. Covers launch XML syntax, arguments, parameters, node configuration, includes, conditionals, namespaces, remapping,...
UX心理学に基づくUIデザインスキル。UIコンポーネント設計時、フォーム設計時、ユーザーフロー設計時、UXレビュー時に使用。認知心理学・行動経済学の原則を適用して使いやすいインターフェースを設計する。
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库,同一仓库的多个技能可能共享相同数值;它反映仓库关注度,不代表单个技能的安装量或质量评分。