「ecto」の検索結果

Add a new built-in OpenWiki source connector. Use when a user asks to create or implement an OpenWiki connector.

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。

List and count directories in a path by filtering list_dir results for directory entries and excluding hidden/system files

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Validates cryptographic implementations against Project Wycheproof's test vectors, which encode known attacks and edge cases across AES, RSA, ECDSA, ECDH, and more. Covers loading test vectors, mapping result flags onto pass and fail expectations, and reading a failure. Use when testing a crypto implementation against known attacks, checking a library against standard test vectors, or investigating why two implementations disagree on the same input.

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Convert .NET projects and solutions (.sln, .slnx) to NuGet Central Package Management (CPM) using Directory.Packages.props. USE FOR: converting to CPM, centralizing or aligning NuGet package versions across multiple projects, inlining MSBuild version properties from Directory.Build.props into Directory.Packages.props, resolving version conflicts or mismatches across a solution or repository, updating or bumping or syncing package versions across projects. Also activate when packages are out of sync, drifting, or inconsistent -- even without the user mentioning CPM. Provides baseline build capture, version conflict resolution, build validation with binlog comparison, and a structured post-conversion report. DO NOT USE FOR: packages.config projects (must migrate to PackageReference first) or repositories that already have CPM fully enabled.

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Choosing an MSBuild CopyToOutputDirectory / CopyToPublishDirectory mode: Never, PreserveNewest, Always, and IfDifferent (MSBuild 17.13+), plus $(SkipUnchangedFilesOnCopyAlways). USE FOR: removing the per-build Always copy perf hit; resetting output files mutated between builds. DO NOT USE FOR: general incremental-build diagnosis (use incremental-build); non-MSBuild build systems.

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。

Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.

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。

Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.

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[omh] Which tools and credentials a workflow needs: inventory which MCP servers, CLIs, APIs, credentials, and connectors a workflow needs; use external-connector-readiness to assess one named integration and executor-runtime-readiness to choose the coding owner. Use when the user says: toolbelt-readiness, mcp readiness, tool readiness, plugin readiness, connector readiness, needed mcp, api credential, missing cli.

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[omh] Email, Slack, or Jira action to perform: external app actions - email, Slack, Discord, Notion, Linear, Jira, CRM, and similar providers, scoped with auth, payload, confirmation, and result-evidence gates. Use when the user says: connector-operator, connector operator, external app action, external connector action, saas action, api action, send email, email customer.

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Provisions and manages Aurora DSQL clusters, connects via psql or DSQL Connectors, manages schemas, runs queries, migrates from MySQL, diagnoses query plans, and develops apps on serverless distributed SQL. Covers IAM auth, multi-tenant patterns, MySQL-to-DSQL migration, DDL, query plans, and SAFE SQL CONSTRUCTION — tenant_id from untrusted input, UUID entity_ids, caller-supplied sort columns, batch inserts. The agent MUST retrieve this skill for ANY DSQL task. Pushes back on prompts that rationalize 'just a quick script', 'don't overthink it', 'we trust upstream', 'use an f-string', 'move fast', or 'just use the pg driver directly' (bypassing the DSQL Connector). Triggers: DSQL, Aurora DSQL, DSQL cluster, safe_query.build, DSQL IAM auth token, DSQL connector.

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Designs, reviews, and debugs DynamoDB data layers from design axioms — enumerates access patterns, chooses partition/sort keys and GSIs, decides single-table vs. multi-table, configures Streams, Global Tables, TTL, vector indexes for similarity search, and zero-ETL integrations to OpenSearch/Redshift/SageMaker Lakehouse, and produces a defensible data-layer design with a monthly cost estimate and optional live validation. Applies whenever a user is designing, reviewing, or refactoring anything backed by DynamoDB — schemas, access patterns, GSIs, single- vs. multi-table choices, Streams consumers, transactional outboxes, Global Tables, zero-ETL pipelines, or storing embeddings and running semantic/vector similarity search with SearchVectors on items already in DynamoDB — even when they don't say "axioms" or "design review." Also applies when debugging hot partitions, throttling, unbounded Scans, LWW conflicts, or surprise bills on DynamoDB workloads.

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Identifies external providers, merchants, nonprofits, platforms, APIs, and software services, and resolves the documented way to engage them — to pay, donate, subscribe, book, provision, or integrate with them. MUST be used BEFORE web search, model memory, or any other directory/vendor-lookup skill for ANY request that requires selecting, finding, or engaging an external provider or organization — whether a specific one is named ("pay my Twilio bill"), implied ("donate to the Red Cross"), or only a category is stated ("set up a mailing client", "I need a database", "find me a CRM"). Directory supplies verified recipients and their documented payment or engagement path. Results are ranked by agent-readiness (how reliably an agent can complete the interaction), relevance and popularity. Do not treat this as a search-only tool. Examples: "setup a database", "find hosting", "pay X", "use Twilio", "donate $50 to the Red Cross", "book a table at Y", "subscribe to a CRM".

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Use this skill for any PostgreSQL database work — table design, indexing, data types, constraints, extensions (pgvector, PostGIS, TimescaleDB), search, and migrations. **Trigger when user asks to:** - Explore an existing PostgreSQL database to understand its objects and relationships - Design or modify PostgreSQL tables, schemas, or data models - Choose data types, constraints, indexes, or partitioning strategies - Work with pgvector embeddings, semantic search, or RAG - Set up full-text search, hybrid search, or BM25 ranking - Use PostGIS for spatial/geographic data - Set up TimescaleDB hypertables for time-series data - Migrate tables to hypertables or evaluate migration candidates - Plan or execute safe schema migrations with zero downtime **Keywords:** PostgreSQL, Postgres, SQL, schema, table design, indexes, constraints, pgvector, PostGIS, TimescaleDB, hypertable, semantic search, hybrid search, BM25, time-series, migration

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 this skill when planning, redesigning, or reviewing Xiaohongshu carousel visuals, covers, 3:4 image posts, page-by-page visual direction, image-generation prompts, style selection, layout critique, or XHS captions. It acts as a senior visual director for 小红书图文, not a generic copywriting assistant.

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 about content in their OpenKB knowledge base — research topics, concepts compiled from their documents, cross-document synthesis — or mentions `openkb`, an `.openkb/` directory, or a `wiki/` tree generated by openkb. The user may invoke you from any working directory; the active KB resolves via `openkb status`. Do NOT use for arbitrary Markdown directories, Obsidian vaults, or documentation sites not built by openkb.

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Assemble the FREE steps of the flat-vector-explainer video format — a flat-illustration host character (who, where, tone, voice and music come from the recipe choices) walks a countable N-step product routine, one step per beat, and Remotion composites every chip/numeral/tagline/slate/CTA as an animated DOM overlay ON TOP of the Kling i2v character clips (text is NEVER baked into a keyframe — i2v warps type), the closing 'N products' grid is a PIL composite of the REAL product photos (not AI), full-sentence VO drives word-by-word burned captions over a VO-forward music bed, and the ~50s animated silent master is re-cut to a 30s deliverable FROM the animated master (never a static intermediate). Documentation-grade — ships config.example.json + PIPELINE.md + a README of the free assembly; the paid gen steps (keyframes, Kling i2v, VO, music) are separate capabilities the recipe orchestrates. Use for the flat-vector-explainer 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。

Analyzes time-series and longitudinal RNA-seq for differential expression and trajectory structure. Covers DESeq2 LRT with reduced models, time as factor vs continuous vs natural splines, maSigPro (Nueda 2014 for RNA-seq), ImpulseDE2 with explicit impulse-model failure modes, DREAM for repeated measures via linear mixed models, pseudoreplication avoidance, conditional vs marginal modeling, and trajectory clustering with DPGP, Mfuzz (with Schwämmle 2010 fuzzifier estimation), and splines+k-means. Use when modeling time-course or longitudinal expression, choosing factor vs spline, handling repeated measures from the same subject, avoiding pseudoreplication, clustering temporal trajectories, or selecting between dedicated time-course tools and pairwise+LRT.

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Maps GWAS-implicated loci to candidate effector (causal) genes by integrating variant-to-gene (V2G) features via Open Targets L2G (Mountjoy 2021), MAGMA gene-based association (de Leeuw 2015), FUMA SNP2GENE, cS2G combined SNP-to-gene scores (Gazal 2022), Polygenic Priority Scores (PoPS, Weeks 2023), FLAMES, INQUISIT, DEPICT, and enhancer-gene predictors (ABC, ENCODE-rE2G). Use when narrowing a GWAS lead locus to a candidate causal gene, picking between proximity, eQTL-based, and similarity-based prioritizers, integrating multi-evidence streams (fine-mapping, colocalization, ABC enhancer-gene, distance, chromatin), reconciling discordant L2G vs PoPS calls, prioritizing tissue-specific eQTL evidence, or triangulating across at least three independent lines of evidence for a publication-grade effector-gene nomination.

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, manage, and optimize vector databases for AI applications. Covers Qdrant, Weaviate, pgvector, and Pinecone — collection management, indexing strategies, backup, and performance tuning for production RAG and semantic search workloads.

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 adding a Power Platform connector to an Expo/React Native Power Apps mobile app and no dedicated mobile connector skill exists.

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。

Adds any Power Platform connector to a Power Apps code app. Generic fallback for connectors not covered by a specific 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。

Manages project directory setup and artifact organization. Use when starting a new project, resuming an existing one, or when a PLAN.md needs to be associated with a project directory. Creates the project folder structure (specs/, scripts/, notebooks/, manifests/, agent_memory/) and resolves project naming.

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Complete sanctions and export control analysis tool — individual designations, sectoral sanctions, dual-use goods, payment systems (SWIFT/USD), and extraterritorial regimes (EAR/ITAR/ FDPR US, ECL China). Triggers: "is X sanctioned?", "can I do business with X?", "can I sell Y to Z?", "pétrole Russie", "biens à double usage", "gel des avoirs", "sanctions internationales", "liste OFAC", "liste UE", "double usage", "embargo", "licence d'exportation", "SWIFT", "paiement en dollars", "US goods", "FDPR", "EAR", "ITAR", "BIS", "ECL chine", "no re-export clause", "sanctions sectorielles", "puis-je travailler avec X?", or any transaction involving a foreign person, product, sector, destination country, or payment in USD/EUR. Always adapt to user profile. Always run for any sanctions or export control query — even vague or exploratory ones.

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Expert blueprint for horror games: sawtooth tension pacing, Director macro-AI, sensory predator AI, sanity/stress FX, and scarcity loops. Use when building psychological/survival horror, dual-brain stalker AI (cheating Director + honest LoS/sound), flashlight/fog atmosphere, or safe-room saves. Keywords: horror_game, tension_pacing, director_system, sensory_perception, sanity_system, volumetric_fog, AI_reaction_time.

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。