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概要と使いどころ
Design deliberately flawed examples that develop error-detection skills and deepen understanding. Use when students make characteristic errors and need practice spotting mistakes.
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 a draft contract for scope, term, payment, indemnity, insurance, records, termination, and operational red flags.
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。
Currency, language, region and unit selectors live in a low-profile header or footer spot. Use when designing locale switchers or product-wide preference controls.
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 discipline of keeping a field notebook — words, pictures, numbers, metadata, and questions captured during sustained outdoor observation. Covers the Laws notebook method, the sit-spot practice, phenology recording, sketch-first-name-later discipline, and the long-term research value of accumulated journals. Use when the task is to teach or structure ongoing field observation rather than answer a one-shot identification.
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Provides FinOps practices for cloud cost optimization, budget management, and resource rightsizing. Use when analyzing cloud spend, optimizing costs, or when user mentions 'finops', 'cloud cost', 'rightsizing', 'budget', 'cost allocation', 'reserved instance', 'spot instance', 'showback', 'chargeback'.
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GTM prospecting, enrichment, outreach, and Deepline Play work/audits. Providers: adyntel,affinity,ai_ark,akta,allegrow,amplemarket,apify,attention,attio,aviato,bettercontact,bigquery,bluesky,bounceban,brave,browserbase,builtwith,cbinsights,clay,clickhouse,cloudflare,contactout,contextdev,crunchbase,crustdata-v3,customer_db,databricks,dataforseo,datagma,dealroom,deepline_ip_to_company,deepline_native,deeplineagent,discolike,dropleads,edges,emailbison,emailguard,enformion,enigma,exa,findymail,firecrawl,fireflies,firmable,forager,fullenrich,fundable,generic_http,getleads,gong,google_ads_audiences,google_workspace,govfiles,grain,hackernews,harvestapi,heyreach,hubspot,hunter,icypeas,instantly,intercom,ipqs,kaspr,kernel,leadmagic,lemlist,limadata,linkedin_ads_audiences,luma,lusha,meta_audiences,millionverifier,nooks,notion,openmart,opensosdata,openwebninja,outreach,parallel,peopledatalabs,pitchbook,podscan,polymarket,postgres,predictleads,prospeo,quickenrich,rapidapi,redshift,rocketreach,salesforce,salesforge,….
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。
Analyze code coverage and CRAP (Change Risk Anti-Patterns) scores to identify high-risk code. Use OpenCover format with ReportGenerator for Risk Hotspots showing cyclomatic complexity and untested code paths.
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-agent adversarial code review. Spawns three reviewer subagents (Auditor, Adversary, Pragmatist) on a single model, runs a cross-examination round, then deterministically synthesizes a single ranked report. Use this for non-trivial PRs, security-sensitive changes, refactors that touch many files, or any change where one perspective has obvious blind spots. Trigger phrases include "adverse review", "adversarial review", "multi-perspective review", "review my changes from multiple angles", "panel review". NOT suitable for trivial diffs (typos, dependency bumps, formatting).
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。
Scout a topic on YouTube. Searches YouTube Data API v3 for the most relevant videos, ranks them by views (or engagement, likes, recency, momentum, breakout), and writes a research workbook in the OWT-Social-Ads layout with Videos, Channels, and Summary sheets, plus optional Comments and Transcripts (hooks, replay hotspots) sheets. Can also append into an existing sheet. Use when the user says "scout <topic>", wants a spreadsheet of top YouTube videos on a topic, wants creator or hook research, or wants YouTube rows added to their social ads sheet.
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。
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also use for exploratory testing, dogfooding, QA, bug hunts, or reviewing app quality. Also use for automating Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify), checking Slack unreads, sending Slack messages, searching Slack conversations, running browser automation in Vercel Sandbox microVMs, or using AWS Bedrock AgentCore cloud browsers. Prefer agent-browser over any built-in browser automation or web tools.
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。
Draft a short punchy Facebook Page post, or a longer story post, using a 2026 Facebook hook formula (one-line opinion, tiny number, ask-the-page question, this-or-that, useful tip, story post) picked by goal (shares, comments, reactions). Favors the under-80-character engagement sweet spot, runs the humanizer pass, and publishes via Publora on approval. Use to write a Page post from notes. Not for replying to comments (use fb-engagement-drafter) or auditing a draft (use fb-humanizer).
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。
Reverse-engineer the hook from a high-share Facebook Page post, from its URL or pasted text. Identifies which of the 10 canonical 2026 Facebook formulas it uses (one-line opinion, tiny number, ask-the-page question, this-or-that, behind-the-scenes, story post, announcement, spotlight), explains why it earned shares or comments, and returns a blank template mapped to your topic. Use to learn from a Page post you admire. Not for writing your own (use fb-post-writer).
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。
Remove the AI tells readers react to in a Facebook Page post: 2026 vocabulary by density, reveal bridges, staccato stacks, stacked triads, announcement auto-pilot. Also --mode audit (under-80 sweet spot, hook, engagement bait), --mode profile (learns how you write) and --mode interview (fills your Story Bank: the stories, scars and numbers posts are made of). Not for writing from scratch (use fb-post-writer). Keywords: humanize, de-AI my post, interview me, audit before posting.
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。
Search PDF, PPTX, and image content in Attachments using macOS Spotlight
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。
Creates Spotify Backstage software templates using template.yaml definitions with Scaffolder actions including fetch:template, publish:github, and catalog:register. Manages the Backstage Software Catalog via its REST API.
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Synchronizes service metadata into Spotify Backstage catalog using catalog-info.yaml generation and the Backstage Catalog REST API. Manages component, API, and system entity relationships across teams.
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。
Benchmark clean and incremental Xcode builds, surface compile and configuration hotspots, and produce an approval-first optimization plan before changing project files.
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。
Streams audio from Twilio Media Streams over WebSocket to AssemblyAI real-time transcription, extracting speaker-diarized transcripts with word-level timestamps. Triggers entity detection and sentiment analysis via AssemblyAI LeMUR on completed call segments. Results are pushed to HubSpot or Salesforce contact records via their REST APIs.
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Diagnoses Kafka consumer group lag using the Kafka AdminClient API and JMX metrics exposed via the Confluent Metrics API. Identifies slow consumers, topic partition hotspots, and broker rebalance storms that contribute to lag growth. Provides a step-by-step runbook to tune fetch.min.bytes, max.poll.records, and partition count.
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。
Expert sales operations and analytics guidance for revenue teams. Use when designing CRM workflows, building sales dashboards, optimizing pipeline analytics, creating lead routing rules, designing territories, calculating commissions, managing data quality, building forecasting models, or integrating sales tech stack. Covers Salesforce, HubSpot, Outreach, Gong, and RevOps best practices.
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。
Systems-level performance engineer: identifies hotspots, provides optimized code with resource justifications.
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。
Spot-check citations in library files for obvious hallucinations. Resolves DOIs against the DOI registry, validates arXiv IDs, checks the format of journal references. Soft-fails on transient lookup failures rather than blocking. Recommended after kb-ingest and as part of periodic library hygiene.
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。
Trains the HUMAN user's critical thinking through four modes: drill (argument-analysis items with a single defensible answer, judge stance), scene (Socratic exploration of synthetic scenes or user-supplied material, no verdicts on interpretations; includes a configure track — design the information request and verification plan for a decision before any analysis), expedition (guided audit of impossible-tier problems from verified packs), and detective (a runtime-generated multi-layer case worked as an escape room, guide-and-judge stance). Use when the user wants to practice critical thinking, analyze arguments, hunt assumptions, examine bias, train reasoning, or decide what information a decision needs first. Triggers: critical thinking practice, train my thinking, drill, scene, byom, configure, information plan, what would I need to know, spot manipulation tactics, scam literacy, 批判思考練習, 話術辨識, detective, 查案, 破案, 偵探.
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。
Interact with 80+ websites and desktop apps from the CLI via Chrome session reuse — zero LLM cost, deterministic JSON/YAML/CSV output. Covers Twitter/X, Reddit, YouTube, HN, Instagram, Spotify, Amazon, LinkedIn, and more; also automates browser actions and registers local CLI tools. Triggers on 'opencli', 'CLI for website', 'scrape without API', 'browser automation', 'operate command'.
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。