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概要と使いどころ
[omh] Recurring Hermes job on a schedule (cron, digests): design recurring Hermes operations with schedule, delivery, silence policy, context chain, and prepared-vs-observed status. Use when the user says: automation-blueprint, scheduled ops, scheduled operation, scheduled operations, automation blueprint, cron blueprint, cron-ready, recurring ops.
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 2500+ curated ChatGPT and LLM open-source repositories. Use when the user asks to find tools, libraries, or repos related to ChatGPT, LLMs, RAG, agents, langchain, NLP, AI development, or any open-source AI tooling.
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 2500+ curated ChatGPT and LLM open-source repositories. Use when the user asks to find tools, libraries, or repos related to ChatGPT, LLMs, RAG, agents, langchain, NLP, AI development, or any open-source AI tooling.
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。
Azure Identity library for .NET. Authentication library for Azure SDK clients using Microsoft Entra ID. Use for DefaultAzureCredential, managed identity, service principals, and developer credentials. Triggers: "Azure Identity", "DefaultAzureCredential", "ManagedIdentityCredential", "ClientSecretCredential", "authentication .NET", "Azure auth", "credential chain".
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 visualize finance logic diagrams (e.g., Draw.io XML) to explain complex finance transmission chains or finance logic flows.
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。
Fetch the latest financial signals and transmission-chain analyses from DeepEar Lite. Use when the user needs immediate insights into financial market trends, stock performance factors, and reasoning from the DeepEar Lite dashboard.
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。
Navigate protein structure hierarchy using Biopython Bio.PDB SMCRA model. Use when accessing models, chains, residues, and atoms, iterating over structure levels, or extracting sequences from PDB 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。
Specialized lipidomics analysis for lipid identification, quantification, and pathway interpretation. Covers LC-MS lipidomics with LipidSearch, MS-DIAL, and LipidMaps annotation. Use when analyzing lipid classes, chain composition, or lipid-specific pathways.
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。
Infer pathogen transmission networks and identify likely transmission pairs using TransPhylo and outbreak reconstruction algorithms. Estimate who-infected-whom from genomic and epidemiological data. Use when investigating outbreak transmission chains or identifying superspreaders.
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。
Judge whether a market FAILED to react to news favorable to a crowded speculative position — step 2 of Jason Shapiro's COT contrarian process. Consumes a cot-contrarian-detector report (or an explicit direction) plus a Claude-curated events JSON, fetches the underlying price series with a documented fallback chain, and produces a fail-closed CONFIRMED / NOT_CONFIRMED / INSUFFICIENT_EVIDENCE verdict using a statistically validated drift-significance test (not a naive failure-ratio, which false-confirms on pure noise). Generic beyond COT — reusable for PEAD and macro-crowding news-failure checks. Use when the user asks to check news-failure confirmation, whether a crowded market "shrugged off" good/bad news, or wants to run Shapiro step 2 on a CROWDED_LONG/CROWDED_SHORT market.
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。
Converts agent definitions between frameworks — exports to Claude Code, OpenAI, CrewAI, Lyzr, and GitHub Models formats, and imports from Claude, Cursor, and CrewAI projects. Use when the user wants to convert an agent, migrate to another framework, export to LangChain/AutoGen/CrewAI, or import from existing automation 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。
Use when the user asks to "map our positioning", "name our competitive alternatives", or "pick a beachhead segment for the launch"; produces a Dunford-style positioning canvas — named competitive alternatives (including spreadsheet and status quo), unique attributes (verifiable, or routed to the claims ledger), value themes (attribute→benefit→value chains), a target beachhead segment scored on serviceability / pain intensity / reachability, and a one-sentence onlyness statement — the sole upstream of the message house and the entity-signal source for the canonical entity profile. Not for the message house or per-channel launch copy — use message-house-builder; not for audience/persona profiling itself — use audience-mapper; not for SEO keyword positioning — use keyword-research. 定位画布/竞争替代品/独特价值/滩头细分
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 the user asks to "run a launch retro / post-mortem", "compare launch results vs targets by channel", or "decide what to keep or kill for the next launch"; produces a structured D1/W1/M1 retrospective — a per-channel actual-vs-target table (UTM-attributed own analytics as the truth column, platform self-reported numbers as reference, every figure labeled Measured / User-provided / Estimated), a 5-Whys chain on the single largest miss, keep / kill / change decisions per channel, 3-5 actionable learnings for the next launch, and an outcome snapshot submitted to the launch registry. Not for return math (CPA / ROI) — use roi-calculator; not for the stakeholder-facing report writeup — use report-generator; not for a metric deep-dive — use performance-analyzer. 发布复盘/渠道归因/5-Whys/keep-kill
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。
Migrate workloads from Google Cloud Platform to AWS — plus AI and agentic workloads from any provider. Triggers on: migrate from GCP, GCP to AWS, move off Google Cloud, migrate Terraform to AWS, migrate Cloud SQL to RDS, migrate GKE to EKS, migrate Cloud Run to Fargate, migrate App Engine to Elastic Beanstalk, migrate from OpenAI to Bedrock, move off OpenAI, switch from ChatGPT API to AWS, migrate from Gemini to Bedrock, migrate LangChain to Bedrock, migrate LangGraph to AWS, migrate agentic workloads to AWS, move AI workloads to AWS, migrate my AI app to AWS. Runs a 6-phase process: discover GCP resources from Terraform, app code, or billing exports, then clarify, design, estimate costs, generate artifacts, and collect feedback. Clarify must finish before Design, Estimate, or Generate. Do not use for: Azure migrations (see azure-to-aws), on-premises migrations, AWS-to-GCP reverse migration, general AWS architecture advice without migration intent, or GCP-to-GCP refactoring.
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。
Audit a target's CORS posture — Access-Control-Allow-Origin handling, reflected-origin bypass, credentials+wildcard mismatch, preflight OPTIONS behavior, Vary header correctness. Use when: a third-party integration is failing CORS preflight and someone proposes "just set Allow-Origin to *" as the fix, OR your bug-bounty inbox has a credential-reuse exploit chain. Threshold: any reflection of arbitrary Origin into Allow-Origin, Allow-Credentials:true with wildcard origin (browser-rejected combo but server config wrong), missing Vary:Origin on per-origin responses, preflight cached over 86400s, OR Allow-Origin trust of attacker- controlled subdomain pattern. Trigger with: "audit cors", "check cors policy", "cors bypass", "preflight check".
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 Apify datasets, key-value stores, and request queues programmatically, and orchestrate multi-Actor pipelines. Use when you need to read or write Apify datasets, export scraped data to CSV/JSON/XLSX, store config or binary artifacts in a key-value store, manage a resumable request queue, chain Actors into a scrape → transform → export pipeline, or monitor Actor run status and cost. Trigger with "apify dataset", "apify key-value store", "apify storage", "export apify data", "apify pipeline", "apify request queue".
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。
Monitor blockchain mempools for pending transactions, gas analysis, and MEV opportunities. Use when analyzing pending transactions, optimizing gas prices, or researching MEV. Trigger with phrases like "check mempool", "scan pending txs", "find MEV", "gas price analysis", or "pending swaps".
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 and secure Alchemy credentials, browser access, wallet authority, webhook verification, and untrusted chain data. Use when securing an Alchemy-backed application. Trigger with "secure Alchemy", "Alchemy API key exposure", or "verify an Alchemy webhook".
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。
Deploy an Alchemy-backed service through environment-scoped credentials, chain assertions, canaries, and rollback gates. Use when promoting an integration to hosted environments. Trigger with "deploy Alchemy integration", "Alchemy production deploy", or "promote an Alchemy service".
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。
Operate Alchemy Notify webhooks with raw-body HMAC verification, idempotent intake, durable processing, and safe lifecycle changes. Use when implementing or repairing blockchain event delivery. Trigger with "Alchemy webhook", "Alchemy Notify", or "verify X-Alchemy-Signature".
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。
Build an NFT discovery workflow with Alchemy NFT API v3 and isolate typed on-chain reads through viem. Use when creating collection explorers or ownership checks. Trigger with "Alchemy NFT API", "NFT collection explorer", or "read an NFT contract".
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。
Establish a deterministic local EVM development loop with pinned forks, synthetic fixtures, and bounded Alchemy usage. Use when adding local chain tests or repairing flaky fork-based development. Trigger with "Alchemy local dev", "Hardhat fork with Alchemy", or "pin a mainnet fork".
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。
Prompt engineering patterns including structured prompts, chain-of-thought, few-shot learning, and system prompt design
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。
Bug-fix discipline — every defect has an etiology, the chain of cause that produced the observable fault; trace it before patching. Errors only grow: a bandaid leaks unless genuinely localized and leak-free. Walk the diagnostic ladder (presentation → proximate cause → API contract → isolated or systemic) before writing the fix. Use when authoring or reviewing any bug fix, regression patch, "quick fix" PR, or when deciding whether to ship, defer, or refactor.
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。