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概要と使いどころ
Control an OctoPrint 3D printer over its local REST API: print jobs, temperatures, file uploads, and gated raw G-code. Trigger phrases: octoprint, 3d printer, start print, pause print, nozzle temperature, bed temperature, gcode.
日本語の概要は準備中です。原文の説明を表示しています。
Control a Klipper 3D printer through Moonraker: print jobs, file uploads, emergency stop, smart plugs, and gated raw G-code. Trigger phrases: moonraker, klipper, mainsail, fluidd, start print, pause print, emergency stop.
日本語の概要は準備中です。原文の説明を表示しています。
Generate media with fal.ai: images, video, audio, music on one key. Submit jobs to 100s of models, poll status, fetch results, upload files. Trigger phrases: fal.ai, fal, run a fal model, flux pro on fal, kling video via fal.
日本語の概要は準備中です。原文の説明を表示しています。
Debugs failing GitHub Actions CI runs for PostHog PRs, commits, and branches, and answers broad CI-health questions ("is CI red?", "is master green today?", "what's broken right now?"). Use when the user asks why CI is red, asks for the current CI or master status, or mentions a failing check, GitHub Actions run, Depot runner, workflow, job, shard, merge queue kick, flaky test, lint failure, typecheck failure, snapshot diff, migration check, generated types drift, or skills build failure. Start with the `hogli ci:insights` digest (cross-run CI history from engineering analytics), then guides read-only inspection, failure classification, smallest local reproduction with hogli, and safe reporting without rerunning CI or posting to GitHub. Running unattended as the "Master-red diagnosis" workflow: see references/master-red-incident.md.
日本語の概要は準備中です。原文の説明を表示しています。
Guides an agent through reproducing, root-causing, fixing, and validating flaky tests in the PostHog monorepo. Use when a test fails intermittently in CI but passes on rerun or locally, when `hogli ci:insights` or the debugging-ci-failures skill classifies a failure as a flaky test, when given a GitHub Actions URL for a flaky job, when asked to check Trunk Flaky Tests for a test, PR, or master, or when asked to deflake, stabilize, or fix a flaky Jest, pytest, or Playwright test. Core discipline: reproduce locally before changing anything, fix the root cause (never mask it with sleeps, retries, or bigger timeouts), and prove the fix with an N-run validation loop sized to the observed failure rate. Stabilizing is not the only valid outcome — the skill also gates whether the test should exist, so deleting a test that catches nothing real, or re-leveling one that flakes because of the level it runs at, are first-class endings.
日本語の概要は準備中です。原文の説明を表示しています。
Multi-cloud orchestration for ML workloads with automatic cost optimization. Use when you need to run training or batch jobs across multiple clouds, leverage spot instances with auto-recovery, or optimize GPU costs across providers.
日本語の概要は準備中です。原文の説明を表示しています。
Use before expensive VidSeeds MCP workflows - seeds, daily MCP call quotas, async jobId polling, when to call vidseeds_get_seed_balance, and avoiding retry loops on MCP_QUOTA_EXCEEDED or insufficient seeds.
日本語の概要は準備中です。原文の説明を表示しています。
Use for VidSeeds MCP thumbnail workflows - generate, poll jobs, edit, restyle, Thumbnail Studio (trends, briefs, subjects, overlay text), apply to a project, publish to YouTube, or thumbnails from a local video file via vidseeds-local.
日本語の概要は準備中です。原文の説明を表示しています。
Use only after explicit Codex `$superloopy:superloopy-backend` or Claude Code `/superloopy:superloopy-backend` invocation, a backend task beginning with leading `loopy` or `루피`, or an active Superloopy loop routes backend work here. Relevant work includes backend application boundaries, APIs, persistence, migrations, transactions, background jobs, caches, events, reliability, security, and runtime database-agent tools. Plain API, server, database, SQL, or agent vocabulary does not activate this workflow.
日本語の概要は準備中です。原文の説明を表示しています。
Manage Jenkins controllers with jk, including jobs, runs, logs, artifacts, credentials, nodes, queues, and plugins.
日本語の概要は準備中です。原文の説明を表示しています。
Spin up a new loop (domain) in a file-based knowledge base — bootstrap the substrate if it's missing, gather the loop's charter, scaffold domains/<loop>/README.md, then do ONE real test run and record it in the loop's Timeline and LOG.md. Use when the user says "set up a new loop", "create a domain", "start a new beat/workstream", or names a recurring job they want the agent to own.
日本語の概要は準備中です。原文の説明を表示しています。
Reactive state and background-work traps: StateFlow conflation, flatMapLatest, job lifecycles, ViewModel bases, WorkManager, backups, crash reporting, logging, Glance widgets. Use when state lags or flips, or work runs twice or never.
日本語の概要は準備中です。原文の説明を表示しています。
Review generated or changed documentation before it ships — READMEs, API references, docstrings, PHPDoc/JSDoc, changelogs, tutorials, and doc sites. Best used reactively after an agent writes or edits docs, after code changes documented behavior, or before publishing docs. Use when the user says 'review the docs', 'is this documentation accurate', 'update the docs', 'write a README', 'document this API', 'add a docstring', or 'add a changelog entry'. Core job: verify every referenced function, flag, endpoint, config key, and code sample against the source; catch docs-vs-code drift; strip filler and unverifiable claims. DO NOT USE for production code review (use clean-code-guard), test review (use test-guard), marketing copy or blog posts, prose style editing of non-technical writing, or documentation site theming.
日本語の概要は準備中です。原文の説明を表示しています。
Use as the entry point for any Agricultural Systems (AgSy) manuscript. Routes to the right AgSy sub-skill based on where you are in the lifecycle and which article type (research paper, short communication, perspective, comment, review) fits. AgSy is a systems-science journal, so the router's first job is to confirm there is a real systems question — interactions, hierarchical levels, trade-offs — not a single-factor field trial. It dispatches; it does not draft content.
日本語の概要は準備中です。原文の説明を表示しています。
Use when drafting the cover letter for an Advanced Materials submission, whose core job is to convince the editor that the work is a genuine materials advance of broad impact worthy of the journal. Argues the impact case; does not fix the science or format the manuscript.
日本語の概要は準備中です。原文の説明を表示しています。
Manages Fabric Variable Library items, including definitions, libraryVariables and valueSets overrides. Covers which consumers can reference a variable and with what syntax -- pipelines, notebooks via notebookutils variableLibrary, Dataflow Gen2, Copy Jobs, shortcuts, UDFs and Plan items -- the active value set per workspace or deployment stage, and Git serialization for CI/CD.
日本語の概要は準備中です。原文の説明を表示しています。
Render a static iOS QWERTY keyboard as inline HTML+CSS sized for the 750-wide 9:16 stage. Includes the 3-suggestion bar, alpha keys, shift/backspace, 123/emoji/space/return row, and the bottom globe+mic strip. No animation logic — slide up/down is the molecule's job (CSS transform on the .keyboard root).
日本語の概要は準備中です。原文の説明を表示しています。
Discover all customers of a given company by scanning websites, case studies, review sites, press, social media, job postings, and more. Use when you need competitive intelligence on who a company sells to.
日本語の概要は準備中です。原文の説明を表示しています。
Track product champions for job changes and qualify their new companies against ICP. Takes a CSV of known champions (with LinkedIn URLs), creates a baseline snapshot via Apify enrichment, then detects when champions move to new companies. Scores new companies on a 0-4 ICP fit scale. Outputs a downloadable CSV of movers with qualification verdicts.
日本語の概要は準備中です。原文の説明を表示しています。
End-to-end champion/buyer/user job change signal composite. Takes a set of known people (past buyers, champions, power users), detects when they move to a new company, researches the new company for ICP fit, and drafts personalized outreach leveraging the existing relationship. Tool-agnostic — works with any people source, detection method, and outreach platform.
日本語の概要は準備中です。原文の説明を表示しています。
People, company, investor, and job search with LinkedIn data enrichment
日本語の概要は準備中です。原文の説明を表示しています。
Detect buying signals across TAM companies and watchlist personas. Three-phase architecture: (1) free diff-based signals from existing data (headcount growth, tech stack changes, funding rounds), (2) Apify-powered signals (job postings, LinkedIn content analysis, profile changes), and (3) post-processing with dedup, scoring, and lead status updates. Writes signals to Supabase signals table for downstream activation.
日本語の概要は準備中です。原文の説明を表示しています。
Query UniProt's REST API (post-2022 endpoint at rest.uniprot.org) for protein sequences, annotations, GO terms, cross-references, ID mappings, and proteomes. Use when fetching UniProtKB entries, navigating the JSON schema, choosing between UniProtKB/UniRef/UniParc/Proteomes resources, deciding stream vs search endpoint for batch retrieval, running ID-mapping jobs with the async pattern, handling isoform suffixes, or filtering reviewed Swiss-Prot vs auto-annotated TrEMBL. Encodes the legacy URL migration (2022), the new JSON schema layout, and bulk-pull patterns.
日本語の概要は準備中です。原文の説明を表示しています。
Postgres best practices maintained by Supabase, for Postgres running anywhere. Load this skill BEFORE writing or changing anything that lives in a Postgres database: creating or altering tables and columns (including choosing column types), schema design, migrations and declarative schema files, RLS policies and the tests that verify them, indexes, triggers, database functions, queues and scheduled jobs (pg_cron, pgmq), vector/semantic search (pgvector), and restoring dumps (pg_restore) or importing data. Also load it when diagnosing slow queries, high CPU, timeouts, EXPLAIN plans, connection exhaustion, locking, bloat, or rows visible to the wrong user or tenant. This is not just a performance guide — schema, migration, security, and SQL authoring tasks need these rules too, even for a one-column change or a single query.
日本語の概要は準備中です。原文の説明を表示しています。