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Found 225 Skills
Product Management frameworks, methodologies, and best practices library. Provides PM knowledge including prioritization (RICE, MoSCoW), goal setting (OKR, SMART), customer research (JTBD, Personas), and product strategy. Use when needing PM methodology guidance or framework application.
AWS Startups reference content — Activate FAQ, credits guide, programs, partner offers, sample architectures, and hundreds of learn articles spanning generative AI, cloud architecture, cost optimization, security, fundraising, go-to-market, and real-world startup case studies. Use when the user asks factual questions about AWS Activate (eligibility, credits, programs, providers), wants a sample architecture or solution guide, or needs an AWS-curated learn article on a specific startup topic. For copy-paste AI prompts (RAG chatbot, MVP scaffold, security baseline, GPU quota, etc.), see the prompt-library-for-startups skill. Do not use for: account-specific lookups (credits balance, Activate membership status, application status), real-time event listings beyond the events stub, or content not present in the bundled `references/` tree.
Guides technical support engineering—customer ticket investigation, reproduction, log and API analysis, root-cause isolation, workaround communication, engineering escalation with evidence, and knowledge-base fixes for product bugs and integration issues. Use when debugging a customer-reported issue, writing a repro for engineering, analyzing API errors, drafting technical replies, or improving support runbooks—not for CS program design, renewals, or billing ops (customer-ops-specialist), production incident command (incident-management-engineer), building product features (fullstack-software-engineer), or company-wide crisis statements and launch announcements (communication-lead), or exec/VIP and community escalation program design (community-executive-escalations-program-manager). Product how-to, macros, and ticket triage without deep debugging: product-support-specialist.
Compatibility router for the shared optimization knowledge base and the language-specific optimization catalog skills. Use when: (1) selecting which optimization catalog skill to load, (2) the implementation language is not fixed yet, (3) a workflow still references the legacy optimization-catalog skill name, (4) deciding whether a finding is shared or language-specific, (5) updating the generalized knowledge-base structure.
Reference skill for Zoom Virtual Agent. Use after routing to a virtual-agent workflow when implementing web embeds, Android or iOS wrapper integrations, knowledge-base sync, lifecycle handling, or troubleshooting.
Investigate a topic against preserved sources and write a provisional research article under `research/` in a Knowledge Base project (the `knowledge-base` starter pack). Read when asked to research a topic, compare options, synthesize sources, gather evidence, or extend an existing research doc. Carries the full procedure: scan existing coverage, agree a research rubric, capture every source verbatim before analyzing, write the article incrementally so a crash never loses work, cite every claim, and link it back into the graph. Does not promote findings to canonical knowledge — that is the sibling `consolidate-notes` skill, after a decision lands.
Promote existing research into a canonical article under `articles/` in a Knowledge Base project (the `knowledge-base` starter pack). Read when a decision has actually been made and the team wants the source-of-truth written down, or when asked to consolidate, canonicalize, promote research, or supersede an older article. Carries the decision-confirmation gate, the `supersedes:` chain that keeps the evidence trail intact, and the canonical voice. Does not conduct new research — that is the sibling `research-with-sources` skill.
Build a per-target knowledge-base markdown next to the active profile by walking the BSP root and source tree. Use after init-image / init-source; not for editing profile fields.
Knowledge-base steward in the spirit of Niklas Luhmann's Zettelkasten. Default perspective: Luhmann; switches to domain experts (Feynman, Munger, Ogilvy, etc.) by task. Enforces atomic notes, connectivity, and validation loops. Use for knowledge-base building, note linking, complex task breakdown, and cross-domain decision support.
Communications-domain literature review with Claude-style knowledge-base-first retrieval. Use when the task is about communications, wireless, networking, satellite/NTN, Wi-Fi, cellular, transport protocols, congestion control, routing, scheduling, MAC/PHY, rate adaptation, channel estimation, beamforming, or communication-system research and the user wants papers, related work, a survey, or a landscape summary. Search Zotero, Obsidian, and local paper folders first when available, then search IEEE Xplore, ScienceDirect, ACM Digital Library, and broader web in that order.
Implements knowledge graphs for AI-enhanced relational knowledge. Covers ontology design, graph database selection (Neo4j, Neptune, ArangoDB, TigerGraph), entity extraction, hybrid graph-vector architecture, query patterns, and AI integration. Use when implementing knowledge graphs, designing ontologies, extracting entities and relationships, selecting a graph database, or building hybrid graph-vector search. Use for knowledge graph, ontology design, entity resolution, graph RAG, hallucination detection. For architecture selection and governance, use the knowledge-base-manager skill. For document retrieval pipelines, use the rag-implementer skill.
Route durable graph-building requests into one honest mode: assistant-native install, local Python build, incremental refresh, graph query follow-up, or a graphify-style structural fallback for markdown-heavy corpora. Use when the user wants `GRAPH_REPORT.md`, `graph.json`, `graph.html`, repo/corpus relationship tracing, mixed code+docs+asset graphing, or graph-backed architecture understanding that should persist across sessions. Route simple locate/reference work to `codebase-search`, narrative knowledge-base work to `llm-wiki`, and project-memory handoff to `opencontext`.