mova-skill-file-cleanup-snapshot-node-basic-wrapper
Scans a filesystem target and produces ds.file_cleanup_snapshot_v1 (no deletions). Input: env.file_cleanup_snapshot_request_v1.
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Scans a filesystem target and produces ds.file_cleanup_snapshot_v1 (no deletions). Input: env.file_cleanup_snapshot_request_v1.
LLM-only skill that accepts a repository structure dump, README, and notes, and returns a standardized markdown snapshot, condensed memory summary, and human checklist. No external HTTP requests or web search.
Use for deterministic changes, evidence-first delivery, or assembling proof kits with clear safety justification.
Coordinates repo snapshot, gate runs, and optional WF cycle operations for a single station execution.
Normalize a single DPP passport input into lab_battery_passport_extended_v1 (happy-path).
Generate a basic cleanup plan (keep/delete/archive/ask) from a filesystem snapshot; no filesystem changes. Input: env.file_cleanup_plan_request_v1, output: ds.file_cleanup_plan_v1.
Assemble a canonical wf_cycle winner_pack from compare artifacts (deterministic copy, replay check).
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.
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.