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/oracle

@c805268
by shingo imotasimota/agent-skills85 stars
15

Designing and evaluating AI/ML systems: prompt engineering, RAG design, LLM application patterns, AI safety, evaluation frameworks, MLOps, cost optimization. Use for AI pipelines or eval harnesses.

Use this Skill: https://skilld.dev/gh/simota/agent-skills/oracle

This session only. Nothing lands on disk.

referencereference-index.md

≈640 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Oracle Reference Index

Every reference/ file oracle owns, and the condition that makes it worth reading. oracle/SKILL.md keeps only the shared-contract rows and a pointer here.

Read this when you need a reference and the Recipe registry did not already name it, or when scanning what this skill can consult at all.


File Read this when
reference/prompt-engineering.md Designing prompts, deciding what a prompt cannot guarantee, triaging bad output by layer, structured outputs, Claude-specific behavior, or prompt tests.
reference/rag-design-anti-patterns.md Retrieval architecture, chunking, Hybrid Search defaults, or RAG anti-pattern checks.
reference/llm-application-patterns.md Choosing agent patterns, MCP design, tool-use contracts, or caching strategy.
reference/ai-safety-guardrails.md OWASP LLM coverage, guardrail layers, hallucination controls, or PII handling.
reference/evaluation-observability.md Building eval suites, CI gates, tracing, monitoring, or rollout checks.
reference/cost-optimization.md Model routing, caching, batching, effort tuning, cost monitoring, or quality-floor gating.
reference/llm-production-anti-patterns.md Production failure modes, architecture anti-patterns, MCP pitfalls, reasoning compensations.
reference/agent-design.md Application-level LLM agents — tool-use loops, schemas, context/memory, delegation, termination, failure modes.
reference/embedding-strategy.md RAG embedding pipeline — chunking, model selection, vector index, re-ranking, hybrid retrieval.
reference/advanced-tool-use.md The tool catalog is the bottleneck (>=10 tools or >10k tokens of definitions, falling selection accuracy, aggregated MCP servers). Covers tool search, defer_loading, programmatic calling, the advisor tool.
reference/human-ai-trust.md A human decides whether to accept the output — explanation design, over/underreliance and sycophancy metrics, the disagreement policy, verification affordances by risk class, escalation-to-human.
reference/agent-behavior-contract.md How much role, policy, memory, relationship, and character an agent needs — necessity axes, budgets, invariant/parameter/state, spec vs prompt vs enforcement, drift.
_common/OPUS_5_AUTHORING.md Sizing the design, thinking depth at DESIGN, front-loading use case/budget/tier at PROFILE. Critical: P3, P5.

Source: SKILL.md on GitHub

1 warning13d5 checks · Risk SAFE
  • Gen Agent Trust Hub13d

    The 'oracle' skill is a professional AI/ML design and evaluation specialist. It provides comprehensive guidance on architecting prompts, RAG pipelines, and agent systems while enforcing security best practices like OWASP LLM Top 10 compliance. No malicious code, obfuscation, or data exfiltration patterns were detected.

  • Socket13d

    No alerts

  • Snyk13d

    Risk: LOW · No issues

  • Runlayer6mo

    3/8 files flagged

  • ZeroLeaks5mo

    Score: 93/100 · 2 sections analyzed

Signed by skilld at c805268. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 2 days ago.

Activeupdated 2 weeks ago

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