Search Newark, Farnell, and element14 for electronic components — find parts by MPN or distributor part number, check pricing/stock, download datasheets, analyze specifications. One unified API covers all three storefronts (Newark for US, Farnell for UK/EU, element14 for APAC). Free API key, simple query-parameter auth, no OAuth. Datasheets download directly from farnell.com CDN with no bot protection. Sync and maintain a local datasheets directory for a KiCad project, or use batch MPN-list seeding (`--mpn-list`) for bulk workflows without a project. Use this skill when the user mentions Newark, Farnell, element14, needs parts from a non-US distributor, wants to compare pricing across regions, or needs datasheets from a source that doesn't require complex API auth. For package cross-reference tables and BOM workflow, see the `bom` skill.
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。
aklofas/kicad-happy☆ 1,3922026年10月6日 更新
PCBWay PCB fabrication and assembly — turnkey/consigned assembly, design rules, ordering workflow. Alternative to JLCPCB for manufacturing. Use with KiCad. Use this skill when the user mentions PCBWay, needs turnkey assembly (PCBWay sources parts by MPN), has parts not available on LCSC, needs assembled boards with non-LCSC components, wants to compare PCBWay vs JLCPCB, or needs assembly with parts sourced globally rather than from LCSC only. For gerber/CPL export, stencil ordering, and BOM management, see the `bom` skill.
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。
aklofas/kicad-happy☆ 1,3922026年10月6日 更新
Read and control connected cars across brands through the Smartcar API: telemetry, lock/unlock, charge control, navigation. Trigger phrases: smartcar, connected car, lock my car, car charge, car location, odometer.
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。
Anil-matcha/awesome-muse-connectors☆ 1,3602026年10月14日 更新
Cartesia text-to-speech: synthesize speech audio and browse voices. Trigger phrases: cartesia, text to speech, TTS, synthesize voice, voiceover.
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。
Anil-matcha/awesome-muse-connectors☆ 1,3602026年10月14日 更新
Search Mouser Electronics for electronic components — secondary source for prototype orders. Find parts, check pricing/stock, download datasheets, analyze specifications. Use with KiCad for BOM creation and part selection. Also supports batch MPN-list seeding (`--mpn-list`) for bulk datasheet workflows without a KiCad project. Use this skill when the user specifically mentions Mouser, when DigiKey is out of stock or has worse pricing, when comparing prices across distributors, or when searching for parts that DigiKey doesn't carry. For package cross-reference tables and BOM workflow, see the `bom` skill.
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。
hashgraph-online/awesome-codex-plugins☆ 1,3172026年10月14日 更新
PCBWay PCB fabrication and assembly — turnkey/consigned assembly, design rules, ordering workflow. Alternative to JLCPCB for manufacturing. Use with KiCad. Use this skill when the user mentions PCBWay, needs turnkey assembly (PCBWay sources parts by MPN), has parts not available on LCSC, needs assembled boards with non-LCSC components, wants to compare PCBWay vs JLCPCB, or needs assembly with parts sourced globally rather than from LCSC only. For gerber/CPL export, stencil ordering, and BOM management, see the `bom` skill.
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。
hashgraph-online/awesome-codex-plugins☆ 1,3172026年10月14日 更新
Search Newark, Farnell, and element14 for electronic components — find parts by MPN or distributor part number, check pricing/stock, download datasheets, analyze specifications. One unified API covers all three storefronts (Newark for US, Farnell for UK/EU, element14 for APAC). Free API key, simple query-parameter auth, no OAuth. Datasheets download directly from farnell.com CDN with no bot protection. Sync and maintain a local datasheets directory for a KiCad project, or use batch MPN-list seeding (`--mpn-list`) for bulk workflows without a project. Use this skill when the user mentions Newark, Farnell, element14, needs parts from a non-US distributor, wants to compare pricing across regions, or needs datasheets from a source that doesn't require complex API auth. For package cross-reference tables and BOM workflow, see the `bom` skill.
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。
hashgraph-online/awesome-codex-plugins☆ 1,3172026年10月14日 更新
BOM (Bill of Materials) management for electronics projects — the workflow skill that coordinates DigiKey, Mouser, LCSC, element14, JLCPCB, PCBWay, and KiCad skills around a unified BOM lifecycle. Create, update, and maintain BOMs with part numbers, costs, quantities stored as KiCad symbol properties. ALWAYS trigger this skill for any task involving component sourcing, pricing, ordering, distributor searches, BOM export, or fabrication preparation — even if the user names a specific distributor or fab house (e.g. "search DigiKey for...", "generate JLCPCB BOM", "order from Mouser"). This skill analyzes the schematic for sourcing gaps, recommends which distributor/fab skills to call for each gap, and writes results back as symbol properties — the agent (or user) performs the actual searches via the called skills. Also trigger on phrases like "what parts do I need", "order components", "how much will this cost", "export for JLCPCB", "find parts for this board", "compare pricing", or "check stock".
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。
hashgraph-online/awesome-codex-plugins☆ 1,3172026年10月14日 更新
Use when deciding WHERE to point SEO effort, not how to write a page. Triggers: a new site or brand with no rankings and no authority ("cold start", "starting from zero", "nobody knows us"), deciding what to double down on, a page or cluster that ranks but earns nothing, hunting emerging or newly-coined keywords before competitors arrive, "should we build a cluster or one page", "what do we write next", "we get impressions but no clicks", "our traffic plateaued despite publishing", whether to chase a head term at all, or turning any of it into recurring automation. Also use when asked why an SEO effort stalled despite consistent output. NOT for writing an article, keyword expansion mechanics, or auditing a single tactic for penalty risk.
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。
AI-Builder-Club/skills☆ 1,2922026年9月16日 更新
Compose look-and-feel traps: theme and colour tokens, artwork palettes, gradients and scrims, shimmer, glass and particle effects, animation, image loading, charts and stats displays (percent changes, shares, buckets). Use when a visual bands, pops, freezes or misleads.
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。
maxrave-dev/kotlin-footguns☆ 1,2902026年9月25日 更新
Pick the right way to represent a dataset so a reader gets the finding in three seconds — a catalog of 20+ chart and diagram forms with when-to-use and failure modes, plus the encoding decisions that make any of them readable (takeaway headline, direct labels, kill the axis, highlight-and-mute, show the caveat). Style-agnostic — use with whatever palette or design system the destination already has. Use when charting survey results, benchmark data, usage metrics, or research findings for a post, brief, deck, or report, and whenever the default bar chart feels like it's burying the point.
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。
huytieu/COG-second-brain☆ 1,2832026年10月2日 更新
Source authentic, high-res PUBLIC-DOMAIN artwork from museum open-access APIs (Met, Cleveland, SMK, Rijksmuseum, NGA, Art Institute of Chicago, Getty, Smithsonian) instead of AI-generated or generic-stock imagery. The default move whenever a visual needs an aesthetic, credible image (blog heroes, decks, social cards, essay/spec figures). Verified keyless recipes + licensing rules inside.
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。
huytieu/COG-second-brain☆ 1,2832026年10月2日 更新
Use when packaging AISTATS code, data, proofs, simulation scripts, notebooks, random seeds, and logs as anonymous supplementary evidence or public post-acceptance artifacts, even when there is no separate artifact badge. Covers what statistically minded AISTATS reviewers inspect first and how to make Monte Carlo studies turnkey.
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。
brycewang-stanford/Awesome-Journal-Skills☆ 1,2562026年9月27日 更新
Use when targeting Earth and Planetary Science Letters (EPSL) or deciding whether a quantitative solid-earth or planetary-science manuscript fits this venue. Encodes the journal's broad-interest process-science fit, the quantitative geochemistry/geophysics evidence bar, Elsevier house style, official-submission re-check, and desk-reject heuristics.
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。
brycewang-stanford/Awesome-Journal-Skills☆ 1,2562026年9月27日 更新
Use when targeting Communications Earth & Environment or deciding whether an earth, environmental, or planetary-science manuscript fits this venue. Encodes the journal's fit, the solid-and-complete-advance bar, Nature Portfolio reporting/data standards, house style, official-submission re-check, and desk-reject heuristics.
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。
brycewang-stanford/Awesome-Journal-Skills☆ 1,2562026年9月27日 更新
Use when targeting Earth System Science Data (ESSD) or deciding whether an earth-system dataset fits this venue. Encodes the journal's data-paper fit, the open-deposition-with-DOI requirement, quality and reuse-documentation bar, Copernicus house style, official-submission re-check, and desk-reject heuristics.
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。
brycewang-stanford/Awesome-Journal-Skills☆ 1,2562026年9月27日 更新
当你为《电子学报》(Acta Electronica Sinica, AES) 投稿准备代码、数据与硬件设计等研究制品(artifact)的可用性说明时使用。中文学报暂无独立的 artifact evaluation 徽章委员会,本技能说明本刊现状、如何自愿开放代码/数据以增强稿件可信度、如何在正文与附录中规范披露制品、如何在双盲阶段匿名托管仓库、以及电子/信号处理类工作(算法、电路、FPGA、数据集)的制品打包要点。帮助作者在没有强制徽章的前提下最大化《电子学报》稿件的可复现说服力。
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。
brycewang-stanford/Awesome-Journal-Skills☆ 1,2562026年9月27日 更新
Set up a complete outbound email campaign in Smartlead. Asks the user for campaign goal, audience, messaging, schedule, and mailbox allocation. Creates the campaign, adds leads, saves email sequences, sets schedule, and assigns available mailboxes. Use when a user wants to launch email outreach via Smartlead.
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。
gooseworks-ai/goose-skills☆ 1,2522026年10月14日 更新
Find LinkedIn profiles of a specific team or department at a company. Use when asked to get LinkedIn profiles, find team members, or look up people in a particular team/department/group at a company.
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。
gooseworks-ai/goose-skills☆ 1,2522026年10月14日 更新
Assemble a multi-scene GRWM beauty-demo ad from a config — a locked-identity creator applies ~5 products step by step while a SEPARATE ElevenLabs voiceover narrates and every scene cut is snapped to the VO's product-name word-starts (Whisper word-level timestamps), then ~5 Playwright product overlay cards (real PDP-verified taglines) are composited onto the master each on its product-NAME word-start, the SEPARATE VO is mixed on top of a ducked music bed at loudnorm I=-14, clean-white 3-words/cue captions are burned, and the video closes on a flat-lay end card. This is the FREE deterministic assembly stage (re-cut to the VO word-starts, hard-concat, Playwright card render + card composite, VO plus music mix, caption burn, flat-lay end card); the VO, scene clips, product cutouts, and music come from create-music-elevenlabs / create-image-gpt-image-fal / create-video-fal. Use for the glassy-matte-grwm format.
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。
gooseworks-ai/goose-skills☆ 1,2522026年10月14日 更新
Assemble a cartoon / animated / hand-crafted music-video ad from a config — a sung song carries the whole narrative while N per-bar i2v clips (one recurring animated character, one look pack) are each cut to their BAR window from librosa beat-tracking and hard-concatenated on the bar, VEED-whisper white bold-sans captions in the BOTTOM third (Alignment 2, above the logo bug, no pill) burned from the song's word timings re-spelled against the locked lyrics, a persistent brand logo bug held over the body (suppressed on the end card), and closed on a solid-brand-color PIL end card with the song still playing under it — never AI-rendered text. This is the FREE deterministic assembly stage (cut-to-bar + hard concat + logo bug + captions + end card + song mux); the song, character, keyframes, and clips come from create-music-elevenlabs / create-image-fal / create-video-fal. Use for the cartoon-music-video format.
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。
gooseworks-ai/goose-skills☆ 1,2522026年10月14日 更新
Compares Hi-C contact maps between conditions across the right scale -- differential bin-pair contacts (multiHiCcompare, diffHic), differential A/B compartments (dcHiC), differential TAD boundaries (delta insulation), and differential loops (diffloop, DiffHiChIP) -- with distance-stratified between-sample normalization, replicate-aware NB-GLM FDR, HiCRep SCC reproducibility gating, and CNV correction for cancer/aneuploid samples. Use when comparing Hi-C between treatment and control, finding differential contacts/compartments/boundaries/loops, normalizing two maps of unequal depth, choosing a replicate-aware test, gating replicates with SCC, or correcting copy-number artifacts before a tumor-vs-normal comparison.
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。
GPTomics/bioSkills☆ 1,2232026年8月15日 更新
Analyzes species-environment relationships with constrained ordination (CCA, RDA, db-RDA), variance partitioning, indicator species (indicspecies IndVal.g group-equalized), PERMANOVA paired MANDATORILY with PERMDISP (Anderson & Walsh 2013; dispersion confounds centroid tests), Joint Species Distribution Models (HMSC, sjSDM, gjam) with explicit rejection of "residual covariance equals biotic interaction", phylogenetic community ecology (SES_MPD/MNTD), trait-environment via RLQ + fourth-corner with corrected modeltype=6 (Dray 2014), bipartite network metrics (NODF, modularity) with curveball null (Strona 2014), and Mantel-test replacements (dbRDA, GDM) for spatial data. Use when testing how environmental gradients structure communities, identifying habitat indicator taxa, partitioning variance among predictors, deciding whether PERMANOVA significance is location vs dispersion, picking among HMSC/sjSDM/gjam, or replacing Mantel tests for landscape 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。
GPTomics/bioSkills☆ 1,2232026年8月15日 更新
Estimates SNP heritability and partitions it across functional annotations, cell types, and loci from GWAS summary statistics or individual-level genotypes. Implements LDSC, stratified LDSC with the baseline-LD model, Finucane 2018 cell-type prioritization, LDAK SumHer, HDL, HESS local heritability, BOLT-REML, GCTA-GREML, graphREML, and Popcorn cross-population genetic correlation. Use when computing total h2_SNP from summary stats, partitioning heritability across functional categories, prioritizing trait-relevant tissues or cell types from ENCODE/Roadmap chromatin marks, reconciling LDSC vs LDAK enrichment estimates, computing local heritability with HESS, estimating genetic correlation between traits, or producing publication-grade enrichment with calibrated sensitivity to model assumptions.
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。
GPTomics/bioSkills☆ 1,2232026年8月15日 更新