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Prep for a first VC meeting by mapping a founder's pitch deck against the investor's pre-meeting questions, producing an honest assessment of what is answered vs. what is missing, then generating a memo the founder can send ahead of the call. Use when a founder asks for help prepping a first VC meeting, when an investor has shared a pre-meeting question list (e.g. Jess Lin / Work-Bench), or when the user wants a deck reviewed against specific investor expectations.
Generate a portable, self-contained Agent Skill from mature, curated Obsidian wiki pages — turning a cluster of verified knowledge into a reusable "digital expert" (SKILL.md + references/). Use this skill when the user says "/vault-skill-factory", "make a skill from my wiki", "turn these pages into a skill", "generate an agent skill from my vault", "package my notes on X as a skill", "build a domain-expert skill from my wiki", or wants to distill recurring, mature wiki knowledge into a shareable skill. Inspired by OpenKB's "drop in a book → out comes a digital expert" pattern. The factory ONLY reads the vault and WRITES TO A REVIEW DIRECTORY — it never installs skills, never writes into .skills/, and never touches global skill directories.
AI job search command center -- evaluate offers, generate CVs, scan portals, track applications
Keep a system's business logic independent of the technology it talks to, by reasoning about which way dependencies point across a hexagonal / ports-and-adapters / clean-architecture boundary. A system holds three kinds of code — its reason to exist (the business logic), its connections to the outside world, and how it's run (the wiring and entrypoint) — so the question is never "which folder" but "is this the reason, a connection, or how it's run, and what may it depend on?" Use it to scaffold a new system, place a feature, integration, or entrypoint, review how it's shaped, or write an ADR about the layout — and whenever a dependency points the wrong way or you're unsure where something belongs. Language-/framework-agnostic: the kinds map onto whatever names a project uses (app/infra/run, domain/adapters/cmd). Reach for it even when the user never says "hexagonal": "where should this go", "scaffold it ports-and-adapters", "review against hexagonal principles", "which layer owns this" are all signals.
MANDATORY for Flink or Amazon Managed Service for Apache Flink (MSF) questions. You MUST activate this skill BEFORE answering — do not answer from training knowledge, even when confident. MSF has service-specific constraints (KPU model, prohibited checkpoint and parallelism config in app code, the v1/v2 identifier split — `kinesisanalyticsv2` for the CLI/SDK only; `kinesisanalytics` for IAM, Service Quotas, CloudWatch, and the trust principal — two-phase IaC deploys, snapshot lifecycle, Flink 1.x→2.x migration) that override generic Flink knowledge.
Runs SQL analytics on SageMaker Catalog asset metadata tables exported as Apache Iceberg in S3 Tables. Covers governance queries, asset growth tracking, ownership audits, time-travel over catalog state, and metadata quality analysis. Applies when querying catalog inventory, finding assets without descriptions, comparing catalog snapshots, or auditing data ownership. Trigger phrases: catalog inventory SQL, how many assets, assets without descriptions, asset growth over time, who owns this data, catalog governance, data quality audit, catalog analytics.
Build heads-up display (HUD) dashboards for AI coding agents — show context usage, active tools, running sub-agents, and task progress in real-time. Use when: monitoring AI agent activity, building developer tools for AI-assisted coding, creating status dashboards for agent workflows.
Provisions, connects, migrates, and operates Amazon RDS for Db2. Applies when provisioning with IBM customer and site IDs (License Manager, BYOL, GovCloud), connecting over TLS, fixing SQL30082N after Secrets Manager rotation, migration from Db2 LUW (Linux, AIX, Windows, AS400) or z/OS mainframe (ADB2GEN, Q Replication), choosing code page/collation (EBCDIC, CCSID), S3 backup/restore, Multi-AZ and cross-region standby replicas, RDSADMIN procedures, customer-managed KMS BYOK, self-managed Active Directory Kerberos, Db2 audit to S3, minimum IAM, or colocation.
Amazon OpenSearch Service and Serverless across five capabilities — migration (Solr/ES/self-managed OpenSearch into AOS/AOSS, schema/query translation, sizing, cutover); provisioning (domain + AOSS lifecycle, upgrades, storage tiers, FGAC, monitoring); search (vector / semantic / hybrid / RAG with Bedrock connectors); log-analytics (PPL, OSI ingestion, anomaly detection, OpenSearch Dashboards, Splunk/Datadog alternatives); trace-analytics (OTel spans, service maps, Data Prepper). Triggers on OpenSearch, AOS, AOSS, Elasticsearch, ELK, Solr, Lucene, vector / k-NN / semantic / hybrid / neural search, RAG, ELSER, log analytics, observability, Kibana, OSI, OCU, PPL, trace analytics, BM25, eDisMax, schema.xml, ILM, ISM, FAISS, HNSW, Migration Assistant for Amazon OpenSearch Service, Historical Data Migration, Live Traffic Migration, UltraWarm, OR1, Splunk/Datadog alternative, moving off Solr. Picks ONE capability per ask, names instance class + count + shard math, ships query DSL examples.
Evaluates, configures, and migrates workloads to AWS Lambda Managed Instances (LMI). Runs Lambda functions on EC2 instances in the user's account while AWS manages provisioning, patching, scaling, routing, and load balancing. Triggers when queries mention Lambda Managed Instances, LMI, capacity providers, multi-concurrent execution environments, EC2-backed Lambda, persistent Lambda instances, PerExecutionEnvironmentMaxConcurrency, CapacityProviderConfig, cold start elimination via dedicated instances, migrating standard Lambda to managed instances, or cost comparison between standard Lambda and LMI with Savings Plans or Reserved Instances.
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.
Queries S3 object metadata, tracks bucket activity, audits object changes, searches annotations, and analyzes storage metrics using S3 Metadata system tables (journal, inventory, annotation) and S3 Storage Lens tables via Athena SQL. Applies when counting objects, finding recent uploads or deletions, identifying who wrote to a prefix, breaking down storage classes, finding objects by tag, searching annotation content, analyzing storage lens metrics, or enabling S3 Metadata tracking. Prefers system tables over raw S3 APIs (list-objects-v2, head-object) at scale. Trigger phrases: bucket activity, object count, who uploaded, track deletions, storage class breakdown, find by tag, search annotations, storage lens metrics, audit bucket changes.