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Claude Skills by lyonzin
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- Rag Security FirstFor any security-related task — threat triage, incident response, MITRE ATT&CK mapping, CVE lookup, exploit analysis, defensive control validation, red/blue/purple team work — always consult the local corpus first. Assumes the RAG is loaded with security content (cybersecurity preset, MITRE data, threat reports, runbooks). Prevents wasted external threat-intel calls and grounds recommendations in the team's actual playbooks.Votes: 0GitHub stars: 294
- Rag Check FirstBefore answering any technical question, code request, architecture decision, or factual claim, call search_knowledge to check the local corpus. Trigger on any query that could be answered with prior work, indexed docs, ADRs, runbooks, or team context. Prevents hallucination and forces reliance on the indexed knowledge base.Votes: 0GitHub stars: 294
- Rag Cite SourcesEvery technical claim drawn from the local corpus must ship with a source citation formatted as path:line or path:section. Trigger whenever the response quotes, paraphrases, or acts on knowledge that came from a search_knowledge or get_document call. Makes answers auditable and lets the user jump to source in one click.Votes: 0GitHub stars: 294
- Rag Onboard ContextAt the start of every new session or when the topic shifts significantly, probe the knowledge base to learn what is indexed. Calls get_index_stats + list_categories + a couple of exploratory search_knowledge queries. Prevents the agent from operating blind or making wrong assumptions about what the corpus contains.Votes: 0GitHub stars: 294
- Rag Evaluate QualityMeasure retrieval quality using evaluate_retrieval (MRR@5 and Recall@5) and get_index_stats. Use after ingestion, a model or configuration change, or a reported search regression. Compare representative questions against a recorded baseline.Votes: 0GitHub stars: 294
- Rag Index DecisionsAfter making a non-obvious architectural decision, solving a novel bug, agreeing on a coding standard, or reaching a conclusion worth remembering, index it back into the knowledge base so the next occurrence is one search away. Uses add_document or add_from_url. Closes the feedback loop that makes a RAG-backed team compound over time.Votes: 0GitHub stars: 294
- Rag Code ReviewWhen performing code review on a PR, diff, snippet, or "look at this change" request, first consult the corpus for related ADRs, coding standards, prior patterns, and similar files. Grounds review comments in the team's actual decisions instead of generic best practices. Trigger on any review-style request — "review", "look at", "any issues with", "does this make sense".Votes: 0GitHub stars: 294
- Rag Deep DiveThree-step multi-tool workflow — search the corpus, fetch the most relevant document in full, then find similar documents. Use when a single search_knowledge hit is not enough because the user asked a "how does X work end to end" or "explain the pattern" or "give me the full picture" question. Prevents shallow answers on complex topics.Votes: 0GitHub stars: 294
- Rag TroubleshootWhen the user reports a bug, error message, stack trace, unexpected behavior, or "why is this broken" question, search the corpus first for prior occurrences, known fixes, or related runbooks. Prevents re-solving problems the team already solved. Trigger on any error signature, exception name, stack trace snippet, or "why does X fail" query.Votes: 0GitHub stars: 294
- Rag Web FallbackOnly reach for external web search when the local corpus comes back empty or clearly insufficient. Forces the agent to try knowledge-rag first, then explicitly document why it needed to escalate. Prevents wasted API cost, latency, and (in air-gapped deployments) accidental network calls.Votes: 0GitHub stars: 294