← RAG & GenAI CopilotCONTENT HISTORY

Update to RAG & GenAI Copilot

Snapshot Nov 3, 2026 · 00:12 UTC · version 0.2.0

WHAT CHANGED

Declared capabilities changed

Declared skills — Now says: [{"description":"Audit claim-level evidence support, source provenance, citation correctness, conflicting evidence and abstention...

Observed in instructions or declared skills. Runtime behavior has not been tested.

Save RAG & GenAI Copilot and check future changes in Following.

Up to 3 plugins free · no card required.

All fields and original values.

Declared skills

Before

Oct 27, 2026 · 00:42 UTC

[{"description":"Production-focused workflow for designing, debugging, evaluating, securing, and operating RAG and grounded GenAI systems across ingestion, retrieval, reranking, context, citations, observability, latency, and cost.","int...

After

Nov 3, 2026 · 00:12 UTC

[{"description":"Audit claim-level evidence support, source provenance, citation correctness, conflicting evidence and abstention behavior.","interface":{"brand_color":null,"default_prompt":null,"display_name":"audit-citations","icon_lar...

Short description

Before

Oct 27, 2026 · 00:42 UTC

Build and debug production RAG

After

Nov 3, 2026 · 00:12 UTC

Build and debug reliable RAG

Long description

Before

Oct 27, 2026 · 00:42 UTC

Production RAG & GenAI Copilot helps you design, debug, evaluate, secure, and operate retrieval-augmented generation systems. It can trace failures across ingestion, parsing, chunking, indexing, retrieval, reranking, context construction...

After

Nov 3, 2026 · 00:12 UTC

Build, inspect, improve, evaluate and secure retrieval-augmented generation systems using focused production workflows. Diagnose ingestion, parsing, indexing, retrieval, reranking, grounded answers, citations and access-control failures....

Full description

Before

Oct 27, 2026 · 00:42 UTC

Production-focused RAG architecture, debugging, evaluation, security, and reliability.

After

Nov 3, 2026 · 00:12 UTC

Engineering-focused RAG architecture, implementation, debugging, evaluation, security, incidents, and reliability workflows.

Compare saved observations

Download comparison JSON
Full technical diff · 18 changed fields

changed /release/description

BEFORE
"Production-focused RAG architecture, debugging, evaluation, security, and reliability."
AFTER
"Engineering-focused RAG architecture, implementation, debugging, evaluation, security, incidents, and reliability workflows."

changed /release/id

BEFORE
"pluginrel_67eb54147fcc81918725bef6bfc02a8a"
AFTER
"pluginrel_b5bdd76d1acc8191a2f474068a3fe8d6"

changed /release/interface/brand_color

BEFORE
null
AFTER
"#1B2636"

changed /release/interface/capabilities

BEFORE
[
  "Design production RAG architectures for quality, freshness, security, latency, and cost",
  "Debug retrieval and grounded-generation failures from traces, logs, prompts, and evals",
  "Diagnose parsing, chunking, indexing, metadata, filtering, reranking, and context issues",
  "Evaluate retrieval quality, groundedness, citation correctness, abstention, and regressions",
  "Review prompt injection, RAG poisoning, cross-tenant leakage, and authorization risks",
  "Plan low-blast-radius incident containment, verification, rollback, and permanent fixes",
  "Improve hybrid retrieval, query rewriting, reranking, context packing, and source precedence",
  "Design observability for retrieval traces, model calls, citations, latency, tokens, and cost",
  "Compare retrievers, rerankers, models, vector stores, and architecture trade-offs",
  "Use current official documentation for model, vector-store, SDK, security, and platform changes"
]
AFTER
[
  "Design RAG architectures with evidence, freshness, authorization, and evaluation boundaries",
  "Build or improve RAG pipelines when coding tools and project access are available",
  "Diagnose ingestion, chunking, indexing, retrieval, reranking, and context failures",
  "Evaluate ranking, grounded answers, citations, abstention, and regressions by slice",
  "Review data isolation, prompt injection, poisoned documents, and access controls",
  "Plan production containment, safe rollback, and incident recovery",
  "Compare vector search, hybrid retrieval, rerankers, models, and trade-offs",
  "Add tracing for answer evidence, latency, cost, failures, and index freshness",
  "Coordinate real specialist agents where supported; otherwise work sequentially",
  "Prepare regression checks and release evidence without inventing test results"
]

changed /release/interface/composer_icon_url

BEFORE
"https://files.openai.com/content?id=file_00000000488481f5aa1f8c8d62f420e5"
AFTER
"https://files.openai.com/content?id=file_000000002d5081f8be87a783ae3dac72"

changed /release/interface/default_prompt

BEFORE
"Debug why this RAG system is returning the wrong evidence."
AFTER
"Debug this RAG failure using my retrieval traces and identify the first failing layer."

changed /release/interface/default_prompts

BEFORE
[
  "Debug why this RAG system is returning the wrong evidence.",
  "Design a production RAG architecture for this use case.",
  "Build an eval plan for retrieval, grounding, citations, and abstention."
]
AFTER
[
  "Debug this RAG failure using my retrieval traces and identify the first failing layer.",
  "Design a secure production RAG architecture for this corpus and access model.",
  "Create an evaluation plan for retrieval, grounded answers, citations, and abstention."
]

changed /release/interface/developer_name

BEFORE
"Krishna Sathvik"
AFTER
"Tekris Labs"

changed /release/interface/logo_url

BEFORE
"https://files.openai.com/content?id=file_0000000077a082308e071300dbcf0d65"
AFTER
"https://files.openai.com/content?id=file_000000006e6c81f89727a5e18305c2af"

changed /release/interface/long_description

BEFORE
"Production RAG & GenAI Copilot helps you design, debug, evaluate, secure, and operate retrieval-augmented generation systems. It can trace failures across ingestion, parsing, chunking, indexing, retrieval, reranking, context construction, generation, citations, authorization, and evaluation; design practical RAG architectures; build retrieval and groundedness evals; review prompt-injection and data-leakage risks; and improve observability, latency, and cost. It favors measurable evidence, reversible fixes, source-level authorization, and simple architectures over prompt-only fixes or unnecessary complexity."
AFTER
"Build, inspect, improve, evaluate and secure retrieval-augmented generation systems using focused production workflows. Diagnose ingestion, parsing, indexing, retrieval, reranking, grounded answers, citations and access-control failures. Design measurable evaluation sets, reliability plans, incident playbooks, observability and latency/cost trade-offs. Supports practical coding and real specialist-agent delegation when tools are available. This is a skills-only plugin: it does not independently query private indexes, execute production evaluations, access your repositories or deploy changes."

changed /release/interface/privacy_policy_url

BEFORE
null
AFTER
"https://tekrislabs.com/privacy"

changed /release/interface/short_description

BEFORE
"Build and debug production RAG"
AFTER
"Build and debug reliable RAG"

changed /release/interface/terms_of_service_url

BEFORE
null
AFTER
"https://tekrislabs.com/terms"

changed /release/interface/website_url

BEFORE
null
AFTER
"https://tekrislabs.com/"

changed /release/keywords

BEFORE
[
  "rag",
  "genai",
  "retrieval",
  "llm",
  "evaluation",
  "security",
  "observability"
]
AFTER
[
  "rag",
  "genai",
  "retrieval",
  "embeddings",
  "groundedness",
  "citations",
  "evaluation",
  "rag-security",
  "observability",
  "agents"
]

changed /release/onboarding_skill_name

BEFORE
null
AFTER
"production-rag-genai-copilot"

changed /release/skills

BEFORE
[
  {
    "description": "Production-focused workflow for designing, debugging, evaluating, securing, and operating RAG and grounded GenAI systems across ingestion, retrieval, reranking, context, citations, observability, latency, and cost.",
    "interface": {
      "brand_color": null,
      "default_prompt": "Debug why this RAG system is returning the wrong evidence.",
      "display_name": "Production RAG & GenAI Copilot",
      "icon_large_url": null,
      "icon_small_url": "https://files.openai.com/content?id=file_00000000fa4481fd95d32cfe08557ca9",
      "iconography": "code",
      "short_description": "Build and debug production RAG"
    },
    "name": "production-rag-genai-copilot",
    "plugin_release_skill_id": "pluginrsk_6ab42166a8b48191b701ca1a1cc94083"
  }
]
AFTER
[
  {
    "description": "Audit claim-level evidence support, source provenance, citation correctness, conflicting evidence and abstention behavior.",
    "interface": {
      "brand_color": null,
      "default_prompt": null,
      "display_name": "audit-citations",
      "icon_large_url": null,
      "icon_small_url": null,
      "iconography": "search",
      "short_description": "Audit claim-level evidence support, source provenance, citation correctness, conflicting evidence and abstention behavior."
    },
    "name": "audit-citations",
    "plugin_release_skill_id": "pluginrsk_6ae8d394c00c819188606ae8be9d3e8a"
  },
  {
    "description": "Implement or scaffold a RAG pipeline from requirements or existing repository using available coding tools and actual test evidence.",
    "interface": {
      "brand_color": null,
      "default_prompt": null,
      "display_name": "build-rag-system",
      "icon_large_url": null,
      "icon_small_url": null,
      "iconography": "code",
      "short_description": "Implement or scaffold a RAG pipeline from requirements or existing repository using available coding tools and actual test evidence."
    },
    "name": "build-rag-system",
    "plugin_release_skill_id": "pluginrsk_6ae8d395d8088191a3fdbdee95a10b49"
  },
  {
    "description": "Compare RAG retrievers, vector stores, rerankers, frameworks and models on grounded technical criteria rather than hype.",
    "interface": {
      "brand_color": null,
      "default_prompt": null,
      "display_name": "compare-rag-stacks",
      "icon_large_url": null,
      "icon_small_url": null,
      "iconography": "chart",
      "short_description": "Compare RAG retrievers, vector stores, rerankers, frameworks and models on grounded technical criteria rather than hype."
    },
    "name": "compare-rag-stacks",
    "plugin_release_skill_id": "pluginrsk_6ae8d39699bc8191b94bd87f7b1ea9c2"
  },
  {
    "description": "Diagnose wrong or missing evidence, hallucinations, stale knowledge, wrong answers, and RAG quality regressions using traces.",
    "interface": {
      "brand_color": null,
      "default_prompt": null,
      "display_name": "debug-rag",
      "icon_large_url": null,
      "icon_small_url": null,
      "iconography": "radar",
      "short_description": "Diagnose wrong or missing evidence, hallucinations, stale knowledge, wrong answers, and RAG quality regressions using traces."
    },
    "name": "debug-rag",
    "plugin_release_skill_id": "pluginrsk_6ae8d394b9988191977f037d0bdbba3f"
  },
  {
    "description": "Design and troubleshoot RAG source ingestion, parsing, chunking, embeddings, metadata, freshness, and index updates.",
    "interface": {
      "brand_color": null,
      "default_prompt": null,
      "display_name": "design-ingestion-indexing",
      "icon_large_url": null,
      "icon_small_url": null,
      "iconography": "hierarchy",
      "short_description": "Design and troubleshoot RAG source ingestion, parsing, chunking, embeddings, metadata, freshness, and index updates."
    },
    "name": "design-ingestion-indexing",
    "plugin_release_skill_id": "pluginrsk_6ae8d39602d881919f02a422e6dee3b8"
  },
  {
    "description": "Design and optimize search, metadata filters, hybrid retrieval, reranking, query rewriting and context selection.",
    "interface": {
      "brand_color": null,
      "default_prompt": null,
      "display_name": "design-retrieval",
      "icon_large_url": null,
      "icon_small_url": null,
      "iconography": "search",
      "short_description": "Design and optimize search, metadata filters, hybrid retrieval, reranking, query rewriting and context selection."
    },
    "name": "design-retrieval",
    "plugin_release_skill_id": "pluginrsk_6ae8d394e19881918f85242dc962e9da"
  },
  {
    "description": "Build measurable RAG evaluations for retrieval relevance, grounding, citations, abstention, security, latency, and cost.",
    "interface": {
      "brand_color": null,
      "default_prompt": null,
      "display_name": "evaluate-rag",
      "icon_large_url": null,
      "icon_small_url": null,
      "iconography": "chart",
      "short_description": "Build measurable RAG evaluations for retrieval relevance, grounding, citations, abstention, security, latency, and cost."
    },
    "name": "evaluate-rag",
    "plugin_release_skill_id": "pluginrsk_6ae8d396a43c81919686dff0cc8c5ea3"
  },
  {
    "description": "Upgrade legacy RAG repositories, APIs or vector infrastructure while preserving behavior, access controls and evidence.",
    "interface": {
      "brand_color": null,
      "default_prompt": null,
      "display_name": "modernize-rag",
      "icon_large_url": null,
      "icon_small_url": null,
      "iconography": "code",
      "short_description": "Upgrade legacy RAG repositories, APIs or vector infrastructure while preserving behavior, access controls and evidence."
    },
    "name": "modernize-rag",
    "plugin_release_skill_id": "pluginrsk_6ae8d394aa2c8191894dcca96fa80f67"
  },
  {
    "description": "Design traces, logging, metrics, dashboards, and SLO monitoring for production retrieval and grounded-answer systems.",
    "interface": {
      "brand_color": null,
      "default_prompt": null,
      "display_name": "observe-rag",
      "icon_large_url": null,
      "icon_small_url": null,
      "iconography": "chart",
      "short_description": "Design traces, logging, metrics, dashboards, and SLO monitoring for production retrieval and grounded-answer systems."
    },
    "name": "observe-rag",
    "plugin_release_skill_id": "pluginrsk_6ae8d397912881919dbc4dae62589ad7"
  },
  {
    "description": "Improve RAG latency, throughput, token usage and cost without silently degrading correctness or security.",
    "interface": {
      "brand_color": null,
      "default_prompt": null,
      "display_name": "optimize-rag",
      "icon_large_url": null,
      "icon_small_url": null,
      "iconography": "chart",
      "short_description": "Improve RAG latency, throughput, token usage and cost without silently degrading correctness or security."
    },
    "name": "optimize-rag",
    "plugin_release_skill_id": "pluginrsk_6ae8d3977254819186cecc05310970a1"
  },
  {
    "description": "Coordinate actual specialist agents for substantial RAG engineering tasks, with independent review and evidence handoffs.",
    "interface": {
      "brand_color": null,
      "default_prompt": null,
      "display_name": "orchestrate-rag-agents",
      "icon_large_url": null,
      "icon_small_url": null,
      "iconography": "hierarchy",
      "short_description": "Coordinate actual specialist agents for substantial RAG engineering tasks, with independent review and evidence handoffs."
    },
    "name": "orchestrate-rag-agents",
    "plugin_release_skill_id": "pluginrsk_6ae8d3971738819181f18f25a4294751"
  },
  {
    "description": "Design a production RAG architecture including ingestion, freshness, retrieval, access control, citations, monitoring, and rollout.",
    "interface": {
      "brand_color": null,
      "default_prompt": null,
      "display_name": "plan-rag-architecture",
      "icon_large_url": null,
      "icon_small_url": null,
      "iconography": "hierarchy",
      "short_description": "Design a production RAG architecture including ingestion, freshness, retrieval, access control, citations, monitoring, and rollout."
    },
    "name": "plan-rag-architecture",
    "plugin_release_skill_id": "pluginrsk_6ae8d395cc008191ba900dc35fa81213"
  },
  {
    "description": "Route RAG or grounded GenAI design, implementation, debugging, evaluation, operations and security requests to focused workflows.",
    "interface": {
      "brand_color": null,
      "default_prompt": "Help me diagnose a RAG failure using retrieval evidence.",
      "display_name": "RAG & GenAI Copilot",
      "icon_large_url": null,
      "icon_small_url": "https://files.openai.com/content?id=file_00000000499881f69068988c564c8be3",
      "iconography": "code",
      "short_description": "Build and debug reliable RAG"
    },
    "name": "production-rag-genai-copilot",
    "plugin_release_skill_id": "pluginrsk_6ae8d3966844819185d0511e9334deef"
  },
  {
    "description": "Handle active RAG production incidents with safe containment, evidence preservation, scoped recovery and rollback.",
    "interface": {
      "brand_color": null,
      "default_prompt": null,
      "display_name": "respond-rag-incident",
      "icon_large_url": null,
      "icon_small_url": null,
      "iconography": "radar",
      "short_description": "Handle active RAG production incidents with safe containment, evidence preservation, scoped recovery and rollback."
    },
    "name": "respond-rag-incident",
    "plugin_release_skill_id": "pluginrsk_6ae8d395845481918147fa9db3bd1108"
  },
  {
    "description": "Review RAG security threats such as prompt injection, poisoned corpora, tenant leakage, secret exposure and tool misuse.",
    "interface": {
      "brand_color": null,
      "default_prompt": null,
      "display_name": "secure-rag",
      "icon_large_url": null,
      "icon_small_url": null,
      "iconography": "radar",
      "short_description": "Review RAG security threats such as prompt injection, poisoned corpora, tenant leakage, secret exposure and tool misuse."
    },
    "name": "secure-rag",
    "plugin_release_skill_id": "pluginrsk_6ae8d39749a88191b16353b2bb641bb1"
  }
]

changed /release/version

BEFORE
"0.1.0"
AFTER
"0.2.0"
Full snapshot data
{
  "canonical_app_id": null,
  "connector_id": null,
  "created_at": "2026-09-23T19:10:25.607737Z",
  "discoverability": "LISTED",
  "id": "plugins_6ab42163e9048191ab6e8c14258a48c3",
  "is_template": false,
  "is_template_instance": false,
  "is_v2_template": false,
  "name": "production-rag-genai-copilot",
  "release": {
    "app_ids": [],
    "app_manifest": null,
    "app_templates": [],
    "description": "Engineering-focused RAG architecture, implementation, debugging, evaluation, security, incidents, and reliability workflows.",
    "display_name": "RAG & GenAI Copilot",
    "id": "pluginrel_b5bdd76d1acc8191a2f474068a3fe8d6",
    "interface": {
      "brand_color": "#1B2636",
      "capabilities": [
        "Design RAG architectures with evidence, freshness, authorization, and evaluation boundaries",
        "Build or improve RAG pipelines when coding tools and project access are available",
        "Diagnose ingestion, chunking, indexing, retrieval, reranking, and context failures",
        "Evaluate ranking, grounded answers, citations, abstention, and regressions by slice",
        "Review data isolation, prompt injection, poisoned documents, and access controls",
        "Plan production containment, safe rollback, and incident recovery",
        "Compare vector search, hybrid retrieval, rerankers, models, and trade-offs",
        "Add tracing for answer evidence, latency, cost, failures, and index freshness",
        "Coordinate real specialist agents where supported; otherwise work sequentially",
        "Prepare regression checks and release evidence without inventing test results"
      ],
      "category": "Developer Tools",
      "composer_icon_dark_url": null,
      "composer_icon_url": "https://files.openai.com/content?id=file_000000002d5081f8be87a783ae3dac72",
      "default_prompt": "Debug this RAG failure using my retrieval traces and identify the first failing layer.",
      "default_prompts": [
        "Debug this RAG failure using my retrieval traces and identify the first failing layer.",
        "Design a secure production RAG architecture for this corpus and access model.",
        "Create an evaluation plan for retrieval, grounded answers, citations, and abstention."
      ],
      "developer_name": "Tekris Labs",
      "logo_url": "https://files.openai.com/content?id=file_000000006e6c81f89727a5e18305c2af",
      "logo_url_dark": null,
      "long_description": "Build, inspect, improve, evaluate and secure retrieval-augmented generation systems using focused production workflows. Diagnose ingestion, parsing, indexing, retrieval, reranking, grounded answers, citations and access-control failures. Design measurable evaluation sets, reliability plans, incident playbooks, observability and latency/cost trade-offs. Supports practical coding and real specialist-agent delegation when tools are available. This is a skills-only plugin: it does not independently query private indexes, execute production evaluations, access your repositories or deploy changes.",
      "plugin_category_id": "developer tools",
      "privacy_policy_url": "https://tekrislabs.com/privacy",
      "screenshot_urls": [],
      "short_description": "Build and debug reliable RAG",
      "terms_of_service_url": "https://tekrislabs.com/terms",
      "website_url": "https://tekrislabs.com/"
    },
    "keywords": [
      "rag",
      "genai",
      "retrieval",
      "embeddings",
      "groundedness",
      "citations",
      "evaluation",
      "rag-security",
      "observability",
      "agents"
    ],
    "mcp_servers": [],
    "onboarding_skill_name": "production-rag-genai-copilot",
    "requires_local_executor": false,
    "skills": [
      {
        "description": "Audit claim-level evidence support, source provenance, citation correctness, conflicting evidence and abstention behavior.",
        "interface": {
          "brand_color": null,
          "default_prompt": null,
          "display_name": "audit-citations",
          "icon_large_url": null,
          "icon_small_url": null,
          "iconography": "search",
          "short_description": "Audit claim-level evidence support, source provenance, citation correctness, conflicting evidence and abstention behavior."
        },
        "name": "audit-citations",
        "plugin_release_skill_id": "pluginrsk_6ae8d394c00c819188606ae8be9d3e8a"
      },
      {
        "description": "Implement or scaffold a RAG pipeline from requirements or existing repository using available coding tools and actual test evidence.",
        "interface": {
          "brand_color": null,
          "default_prompt": null,
          "display_name": "build-rag-system",
          "icon_large_url": null,
          "icon_small_url": null,
          "iconography": "code",
          "short_description": "Implement or scaffold a RAG pipeline from requirements or existing repository using available coding tools and actual test evidence."
        },
        "name": "build-rag-system",
        "plugin_release_skill_id": "pluginrsk_6ae8d395d8088191a3fdbdee95a10b49"
      },
      {
        "description": "Compare RAG retrievers, vector stores, rerankers, frameworks and models on grounded technical criteria rather than hype.",
        "interface": {
          "brand_color": null,
          "default_prompt": null,
          "display_name": "compare-rag-stacks",
          "icon_large_url": null,
          "icon_small_url": null,
          "iconography": "chart",
          "short_description": "Compare RAG retrievers, vector stores, rerankers, frameworks and models on grounded technical criteria rather than hype."
        },
        "name": "compare-rag-stacks",
        "plugin_release_skill_id": "pluginrsk_6ae8d39699bc8191b94bd87f7b1ea9c2"
      },
      {
        "description": "Diagnose wrong or missing evidence, hallucinations, stale knowledge, wrong answers, and RAG quality regressions using traces.",
        "interface": {
          "brand_color": null,
          "default_prompt": null,
          "display_name": "debug-rag",
          "icon_large_url": null,
          "icon_small_url": null,
          "iconography": "radar",
          "short_description": "Diagnose wrong or missing evidence, hallucinations, stale knowledge, wrong answers, and RAG quality regressions using traces."
        },
        "name": "debug-rag",
        "plugin_release_skill_id": "pluginrsk_6ae8d394b9988191977f037d0bdbba3f"
      },
      {
        "description": "Design and troubleshoot RAG source ingestion, parsing, chunking, embeddings, metadata, freshness, and index updates.",
        "interface": {
          "brand_color": null,
          "default_prompt": null,
          "display_name": "design-ingestion-indexing",
          "icon_large_url": null,
          "icon_small_url": null,
          "iconography": "hierarchy",
          "short_description": "Design and troubleshoot RAG source ingestion, parsing, chunking, embeddings, metadata, freshness, and index updates."
        },
        "name": "design-ingestion-indexing",
        "plugin_release_skill_id": "pluginrsk_6ae8d39602d881919f02a422e6dee3b8"
      },
      {
        "description": "Design and optimize search, metadata filters, hybrid retrieval, reranking, query rewriting and context selection.",
        "interface": {
          "brand_color": null,
          "default_prompt": null,
          "display_name": "design-retrieval",
          "icon_large_url": null,
          "icon_small_url": null,
          "iconography": "search",
          "short_description": "Design and optimize search, metadata filters, hybrid retrieval, reranking, query rewriting and context selection."
        },
        "name": "design-retrieval",
        "plugin_release_skill_id": "pluginrsk_6ae8d394e19881918f85242dc962e9da"
      },
      {
        "description": "Build measurable RAG evaluations for retrieval relevance, grounding, citations, abstention, security, latency, and cost.",
        "interface": {
          "brand_color": null,
          "default_prompt": null,
          "display_name": "evaluate-rag",
          "icon_large_url": null,
          "icon_small_url": null,
          "iconography": "chart",
          "short_description": "Build measurable RAG evaluations for retrieval relevance, grounding, citations, abstention, security, latency, and cost."
        },
        "name": "evaluate-rag",
        "plugin_release_skill_id": "pluginrsk_6ae8d396a43c81919686dff0cc8c5ea3"
      },
      {
        "description": "Upgrade legacy RAG repositories, APIs or vector infrastructure while preserving behavior, access controls and evidence.",
        "interface": {
          "brand_color": null,
          "default_prompt": null,
          "display_name": "modernize-rag",
          "icon_large_url": null,
          "icon_small_url": null,
          "iconography": "code",
          "short_description": "Upgrade legacy RAG repositories, APIs or vector infrastructure while preserving behavior, access controls and evidence."
        },
        "name": "modernize-rag",
        "plugin_release_skill_id": "pluginrsk_6ae8d394aa2c8191894dcca96fa80f67"
      },
      {
        "description": "Design traces, logging, metrics, dashboards, and SLO monitoring for production retrieval and grounded-answer systems.",
        "interface": {
          "brand_color": null,
          "default_prompt": null,
          "display_name": "observe-rag",
          "icon_large_url": null,
          "icon_small_url": null,
          "iconography": "chart",
          "short_description": "Design traces, logging, metrics, dashboards, and SLO monitoring for production retrieval and grounded-answer systems."
        },
        "name": "observe-rag",
        "plugin_release_skill_id": "pluginrsk_6ae8d397912881919dbc4dae62589ad7"
      },
      {
        "description": "Improve RAG latency, throughput, token usage and cost without silently degrading correctness or security.",
        "interface": {
          "brand_color": null,
          "default_prompt": null,
          "display_name": "optimize-rag",
          "icon_large_url": null,
          "icon_small_url": null,
          "iconography": "chart",
          "short_description": "Improve RAG latency, throughput, token usage and cost without silently degrading correctness or security."
        },
        "name": "optimize-rag",
        "plugin_release_skill_id": "pluginrsk_6ae8d3977254819186cecc05310970a1"
      },
      {
        "description": "Coordinate actual specialist agents for substantial RAG engineering tasks, with independent review and evidence handoffs.",
        "interface": {
          "brand_color": null,
          "default_prompt": null,
          "display_name": "orchestrate-rag-agents",
          "icon_large_url": null,
          "icon_small_url": null,
          "iconography": "hierarchy",
          "short_description": "Coordinate actual specialist agents for substantial RAG engineering tasks, with independent review and evidence handoffs."
        },
        "name": "orchestrate-rag-agents",
        "plugin_release_skill_id": "pluginrsk_6ae8d3971738819181f18f25a4294751"
      },
      {
        "description": "Design a production RAG architecture including ingestion, freshness, retrieval, access control, citations, monitoring, and rollout.",
        "interface": {
          "brand_color": null,
          "default_prompt": null,
          "display_name": "plan-rag-architecture",
          "icon_large_url": null,
          "icon_small_url": null,
          "iconography": "hierarchy",
          "short_description": "Design a production RAG architecture including ingestion, freshness, retrieval, access control, citations, monitoring, and rollout."
        },
        "name": "plan-rag-architecture",
        "plugin_release_skill_id": "pluginrsk_6ae8d395cc008191ba900dc35fa81213"
      },
      {
        "description": "Route RAG or grounded GenAI design, implementation, debugging, evaluation, operations and security requests to focused workflows.",
        "interface": {
          "brand_color": null,
          "default_prompt": "Help me diagnose a RAG failure using retrieval evidence.",
          "display_name": "RAG & GenAI Copilot",
          "icon_large_url": null,
          "icon_small_url": "https://files.openai.com/content?id=file_00000000499881f69068988c564c8be3",
          "iconography": "code",
          "short_description": "Build and debug reliable RAG"
        },
        "name": "production-rag-genai-copilot",
        "plugin_release_skill_id": "pluginrsk_6ae8d3966844819185d0511e9334deef"
      },
      {
        "description": "Handle active RAG production incidents with safe containment, evidence preservation, scoped recovery and rollback.",
        "interface": {
          "brand_color": null,
          "default_prompt": null,
          "display_name": "respond-rag-incident",
          "icon_large_url": null,
          "icon_small_url": null,
          "iconography": "radar",
          "short_description": "Handle active RAG production incidents with safe containment, evidence preservation, scoped recovery and rollback."
        },
        "name": "respond-rag-incident",
        "plugin_release_skill_id": "pluginrsk_6ae8d395845481918147fa9db3bd1108"
      },
      {
        "description": "Review RAG security threats such as prompt injection, poisoned corpora, tenant leakage, secret exposure and tool misuse.",
        "interface": {
          "brand_color": null,
          "default_prompt": null,
          "display_name": "secure-rag",
          "icon_large_url": null,
          "icon_small_url": null,
          "iconography": "radar",
          "short_description": "Review RAG security threats such as prompt injection, poisoned corpora, tenant leakage, secret exposure and tool misuse."
        },
        "name": "secure-rag",
        "plugin_release_skill_id": "pluginrsk_6ae8d39749a88191b16353b2bb641bb1"
      }
    ],
    "version": "0.2.0"
  },
  "scope": "GLOBAL",
  "share_url": "https://chatgpt.com/plugins/plugins_6ab42163e9048191ab6e8c14258a48c3?open_in_app",
  "status": "ENABLED"
}

SHA-256 of public snapshot: e8590cb063d21c079432ea41cab932a9fb0be5b430829b26d0e82eefba1433b0