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概要と使いどころ
Set up and orchestrate multi-container Docker applications using docker-compose, including service configuration, networking, volumes, and environment management. Use when the user requests docker compose setup or provides relevant inputs for 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。
Populate databases with realistic, reproducible test data for development, testing, and staging environments. Use when the user requests database seeding or provides relevant inputs for 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。
Plan, execute, document, and retest authorized security assessments of AI agents and multi-agent workflows using safe adversarial cases, synthetic identities, canaries, and evidence-based findings. Use when defining red-team rules of engagement, assessing prompt injection or excessive agency, testing tool and identity boundaries, evaluating memory or cross-agent attacks, scoring a campaign, or verifying remediation in an approved environment.
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Determine the TRUE cause of a failed retort run before attributing it. Ground-truth every failure (run its tests, read its agent logs, inspect its workspace) and classify it as an infrastructure false-fail, a genuine model miss, or an environment issue — never trust the gate verdict or a log signature alone. Use whenever a run is recorded failed (test_coverage=0 / gate fail), a pass rate looks low, or you're deciding whether a "failure" is real before reporting or proceeding.
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。
Think and work like an expert Horticulturist. Use when a task calls for Horticulturist judgment. Reasons from plant-environment-cultural coupling, source-sink carbon partitioning, and chilling/photoperiod thresholds through rootstock-scion matching, DLI/VPD and substrate EC/pH targets, Dynamic/Utah chill models, and CA/MA postharvest setpoints while treating blossom-end rot, bitter pit, tipburn, storage scald, and MRL/PHI breaches as first-class failure modes.
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。
Think and work like an expert Computational Scientist. Use when a task calls for Computational Scientist judgment. Reasons from Roache code/solution verification and ASME V&V 10/20/40 credibility through MMS/GCI, UQ ensembles, and Snakemake/Nextflow/CWL pipelines with conda-lock/Apptainer provenance while treating environment drift, workflow cache staleness, and validation-vs-calibration conflation as first-class failure modes.
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。
Think and work like an expert Developmental Psychologist. Use when a task calls for Developmental Psychologist judgment. Reasons from developmental trajectories, measurement invariance, and familial-environmental context through age-normed instruments (Bayley, WPPSI/WISC, CBCL, MacArthur-Bates CDI), false-belief and violation-of-expectation paradigms, and lme4/lavaan growth models while treating verbal-demand confounding of theory of mind, informative attrition, adult-normed task misapplication, and parent-versus-direct-assessment divergence as first-class failure modes.
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。
Think and work like an expert Crop Scientist. Use when a task calls for Crop Scientist judgment. Reasons from genotype-by-environment-by-management interaction, yield-component partitioning, and phenology-gated critical periods through MET stability analysis (AMMI, Finlay-Wilkinson, GGE biplots), mixed models (ASReml-R, lme4), N-response curves (quadratic-plateau, MRTN), and crop models (APSIM, DSSAT) while treating pseudo-replicated subsamples, single-site yield champions, uncorrected harvest moisture, and weather-during-anthesis confounding as first-class failure modes.
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。
Think and work like an expert Animal Scientist. Use when a task calls for Animal Scientist judgment. Reasons from NRC nutrient requirements, ad libitum intake, energy/protein partitioning, and genotype x environment x management through ration software (CNCPS, NDS, NRC), pen-blocked trials with mixed models (lme4, PROC MIXED), and BCS, NIR, and rumen/BHBA diagnostics while treating intake collapse, milk fat depression, acidosis, heat stress, wrong experimental unit, and violated withdrawal times as first-class failure modes.
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。
Macro regime analysis, bull bear market detection, business cycle analysis, macro environment assessment, interest rate cycle, yield curve analysis, monetary policy, fiscal policy, global macro, central bank posture, credit cycle, recession probability, expansion regime, macro regime shift, stagflation detection
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Use for video-conditioned audio and automated Foley production: adding synchronized sound effects, ambience, impacts, footsteps, cloth, prop, and environmental audio to silent or under-sounded video using video-to-audio models, text-to-sound tools, manual spot lists, editing, rights checks, and QA.
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。
Provider-independent production design direction for AI-generated media. Use when translating narrative, brand, advertising, product, social, film, or worldbuilding intent into sets, locations, props, color and material palettes, era research, graphic and environmental design, continuity bibles, image/video prompt planning, reference strategy, production constraints, iteration notes, handoff specs, and QA.
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 eDNA metabarcoding from raw amplicons to community ecology. Covers QC, primer removal, denoising with OBITools3 or DADA2, contamination filtering, taxonomy assignment, Hill number diversity, and constrained ordination. Use when processing environmental DNA samples for biodiversity assessment or ecological surveys.
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。
Processes environmental DNA metabarcoding data from raw amplicon reads to species occurrence tables using OBITools3, DADA2, and taxonomic assignment against BOLD, MIDORI2, or MitoFish databases. Handles COI, 12S, rbcL, and ITS barcode regions with primer removal, denoising, chimera detection, and contamination filtering via decontam. Includes occupancy modeling (occumb) for detection probability correction. Use when analyzing eDNA from water, soil, or bulk samples for biodiversity monitoring. Not for 16S human microbiome (see microbiome/amplicon-processing).
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 A/B compartments from Hi-C data using cooltools and eigenvector decomposition. Identify active (A) and inactive (B) chromatin compartments from contact matrices. Use when identifying A/B compartments from Hi-C data.
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。
Download large datasets from NCBI efficiently using EPost, history server, batching, rate limiting, and retry logic. Use when bulk-fetching tens of thousands of sequences, pulling all results of a large ESearch, designing reproducible pipelines, comparing E-utilities to NCBI Datasets v2 CLI, or implementing checksum-validated downloads. Encodes WebEnv TTL (~8h), EPost 200-ID limit, retmax caps, parallelization design, and integrity verification.
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。
First-time setup for protein design tools. Use this skill when: (1) User is new and hasn't run any tools yet, (2) Commands fail with "file not found" or "modal: command not found", (3) Modal authentication errors occur, (4) User asks how to get started or set up the environment, (5) biomodals directory is missing or tools aren't working.
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。
How to use the Boundless CLI — the primary interface for the Boundless ZK proof marketplace. Covers requestor, prover, and rewards commands, config, env vars, and the monorepo structure. Use when working with the boundless CLI, submitting proofs, managing provers, staking rewards, or navigating the codebase.
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。
Internal — for Boundless team members only. Deploy Boundless infrastructure to a new blockchain. Creates Pulumi stacks, config files, updates ChainId enum, and wires CI/CD pipelines for staging and prod environments. Use when adding a new chain, deploying to a new network, or setting up new chain infrastructure.
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。
Internal — for Boundless team members only. Audit native ETH, market deposit, prover collateral, and distributor ZKC reserve balances for every operator-managed address (provers, distributor, order generators, signal). Use when the user wants to know which addresses need topping up, asks about the balance of provers/OGs/distributor/signal signers, says something is "running low" or "out of gas", or wants a periodic operational health check on operator wallets. Defaults to prod env (mainnets + prod testnets) — pass `--all` to also include staging.
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。
Internal — for Boundless team members only. Cross-reference Boundless indexer API data, broker telemetry, and service logs to investigate production and staging operational issues. Use when the user wants to understand why slashings happened on prod/staging, diagnose prover or service failures in deployed environments, correlate market events with broker behavior, investigate fulfillment rate drops, look at prover/service logs, or perform any analysis that requires combining on-chain indexer data with off-chain broker telemetry and CloudWatch logs. Also use when the user asks to "investigate", "diagnose", or "find root cause" for prover, service, or market issues on live networks. Do NOT use for debugging local code changes, reviewing PRs, or investigating issues in the codebase itself.
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。
Internal — for Boundless team members only. Query AWS CloudWatch logs for Boundless services (provers, slasher, distributor, order stream, order generator, indexer, signal) on prod/staging environments. Use when the user asks to look at service logs, debug service behavior from log output, search logs for a request ID, or investigate errors using CloudWatch. Do NOT use for debugging local code changes, reviewing PRs, or investigating issues in the codebase itself.
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。
The moi workspace — the web UI the user chats from, extended with agent-authored applets (widgets, views) plus theme & config. Read this FIRST when a message carries a hidden moi-context envelope or the user uses moi vocab such as workspace, applet, widget, view, scratchpad, dashboard, or a `moi` command, or asks to build, edit, customize, or theme the workspace UI or its layout.
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。
Create and fill .agents/qa-project-context.md with the project's tech stack, test frameworks, CI/CD pipeline, environments, quality goals, risk areas, team structure, and conventions. This is the one file every other QA skill reads first, so they skip redundant discovery and give context-aware advice. Use when: "set up QA context," "configure testing," "initialize project," first use of any QA skill. Not for: bootstrapping a brand-new project's QA end-to-end — use qa-start (which calls this skill as its first step). Related: qa-start, risk-based-testing, test-strategy, qa-metrics, playwright-automation.
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。