{"resources":{"explicit":{"id":"explicit","fields":{"content":{"name":"content","type":"\u001bexplicit.content","title":"Explicit content detection","desc":"Harmful or explicit content found in a block of text, using a text-moderation model (KoalaAI/Text-Moderation) that reproduces the OpenAI content-moderation taxonomy across eight harm categories plus a safe class. Select the text with explicit.content(input: \"...\") and read results for the single most likely category. Classification is single-label: the model scores all categories with a softmax and only the highest-scoring one is returned, so each input yields at most one result (none when the top category is the safe class). Useful for moderating model inputs and outputs.","provider":"go.mondoo.com/cnquery/providers/ai","is_implicit_resource":true}},"is_extension":true},"explicit.content":{"id":"explicit.content","name":"explicit.content","fields":{"input":{"name":"input","type":"\u0007","is_mandatory":true,"title":"Text to scan for explicit content","provider":"go.mondoo.com/cnquery/providers/ai"},"results":{"name":"results","type":"\u0019\n","title":"Detected explicit-content match","desc":"At most one entry, holding entity (the highest-scoring category: SEXUAL, sexually explicit content; HATEFUL, hate toward protected groups; VIOLENT, content glorifying violence or suffering; HARASSMENT, content meant to torment or demean; SELF_HARM, content depicting or encouraging suicide or self-injury; SEXUAL_MINORS, sexual content involving anyone under 18; HATE_THREATENING, hateful content that threatens violence against a targeted group; or VIOLENT_GRAPHIC, extremely graphic depictions of death or injury), type (always EXPLICIT_CONTENT), and score (model confidence from 0 to 1). Omitted when the top-scoring category is the safe class, when the input is empty, or when nothing is flagged.","provider":"go.mondoo.com/cnquery/providers/ai"}},"init":{"args":[{"name":"input","type":"\u0007"}]},"title":"Explicit content detection","desc":"Harmful or explicit content found in a block of text, using a text-moderation model (KoalaAI/Text-Moderation) that reproduces the OpenAI content-moderation taxonomy across eight harm categories plus a safe class. Select the text with explicit.content(input: \"...\") and read results for the single most likely category. Classification is single-label: the model scores all categories with a softmax and only the highest-scoring one is returned, so each input yields at most one result (none when the top category is the safe class). Useful for moderating model inputs and outputs.","provider":"go.mondoo.com/cnquery/providers/ai"},"mcp":{"id":"mcp","name":"mcp","fields":{"prompt":{"name":"prompt","type":"\u001bmcp.prompt","title":"Model Context Protocol prompt","desc":"Reusable prompt template an MCP server offers, keyed by name. Includes an optional display title, a description of what the prompt does or when to use it, and the arguments it accepts to fill in the template.","is_private":true,"provider":"go.mondoo.com/cnquery/providers/ai","is_implicit_resource":true},"prompts":{"name":"prompts","type":"\u0019\u001bmcp.prompt","title":"Reusable prompt templates the server offers","desc":"One entry per prompt returned by the server's prompts/list. Empty when the server does not advertise the prompts capability.","provider":"go.mondoo.com/cnquery/providers/ai"},"resource":{"name":"resource","type":"\u001bmcp.resource","title":"Model Context Protocol resource","desc":"Data resource an MCP server makes available as context for a model, keyed by name (for example mcp.resources.where(name == \"config\")). Carries the URI that addresses it, a display title, a description of the content it provides, and the MIME type of that content. Useful for auditing what server-side data a model can pull in as context.","is_private":true,"provider":"go.mondoo.com/cnquery/providers/ai","is_implicit_resource":true},"resourceTemplate":{"name":"resourceTemplate","type":"\u001bmcp.resourceTemplate","title":"Model Context Protocol resource template","desc":"URI template for addressing a family of parameterized server resources, keyed by name. Carries a display title and a description of the resources the template generates. Useful for understanding which dynamic, argument-addressed resources a model can request.","is_private":true,"provider":"go.mondoo.com/cnquery/providers/ai","is_implicit_resource":true},"resourceTemplates":{"name":"resourceTemplates","type":"\u0019\u001bmcp.resourceTemplate","title":"URI templates for parameterized server resources","desc":"One entry per template returned by the server's resources/templates/list, describing families of resources addressed by a URI template. Empty when the server does not advertise the resources capability.","provider":"go.mondoo.com/cnquery/providers/ai"},"resources":{"name":"resources","type":"\u0019\u001bmcp.resource","title":"Data resources the server makes available as model context","desc":"One entry per resource returned by the server's resources/list. Empty when the server does not advertise the resources capability.","provider":"go.mondoo.com/cnquery/providers/ai"},"serverName":{"name":"serverName","type":"\u0007","title":"Name the server reports during the initialize handshake","desc":"Self-reported implementation name from the server's initialize response. Empty when the server does not report one.","provider":"go.mondoo.com/cnquery/providers/ai"},"serverVersion":{"name":"serverVersion","type":"\u0007","title":"Version the server reports during the initialize handshake","desc":"Self-reported implementation version from the server's initialize response. Empty when the server does not report one.","provider":"go.mondoo.com/cnquery/providers/ai"},"tool":{"name":"tool","type":"\u001bmcp.tool","title":"Model Context Protocol tool","desc":"Single tool an MCP server exposes for a model to call, keyed by name (for example mcp.tools.where(name == \"search\")). Fields cover the human-readable description shown to the model, server-declared behavioral annotations, and the input schema describing the arguments the tool accepts. Useful for auditing which capabilities a server grants and flagging tools that can modify state or reach external systems before allowing a model to invoke them.","provider":"go.mondoo.com/cnquery/providers/ai","is_implicit_resource":true},"toolInputSchema":{"name":"toolInputSchema","type":"\u001bmcp.toolInputSchema","title":"Model Context Protocol tool input schema","desc":"JSON Schema describing the arguments a tool accepts. The type is the top-level schema type (typically \"object\"), properties holds the per-argument schema definitions keyed by argument name, and required lists the argument names that must be supplied.","is_private":true,"provider":"go.mondoo.com/cnquery/providers/ai","is_implicit_resource":true},"tools":{"name":"tools","type":"\u0019\u001bmcp.tool","title":"Tools the server exposes for a model to invoke","desc":"One entry per tool returned by the server's tools/list, each carrying a name, description, behavioral annotations, and input schema. Empty when the server does not advertise the tools capability.","provider":"go.mondoo.com/cnquery/providers/ai"}},"title":"Model Context Protocol server","desc":"Capabilities advertised by a connected Model Context Protocol (MCP) server: the tools it exposes for a model to call, the reusable prompts it offers, the data resources it makes available as context, and the URI templates for addressing those resources. Each collection is populated from the server's response to the corresponding list request and is available only when the server declared the matching capability (tools, prompts, or resources) in its initialize handshake, so an empty tools, prompts, or resources list means the server does not advertise that feature. Useful for inventorying and auditing exactly what an MCP server permits a model to do, for example flagging servers that expose state-changing tools or reach external systems.","provider":"go.mondoo.com/cnquery/providers/ai"},"mcp.prompt":{"id":"mcp.prompt","name":"mcp.prompt","fields":{"arguments":{"name":"arguments","type":"\u0019\n","is_mandatory":true,"title":"Arguments the prompt template accepts","desc":"One dict per argument, each with name, an optional description, and a required flag indicating whether the argument must be supplied when requesting the prompt. Empty when the prompt takes no arguments.","provider":"go.mondoo.com/cnquery/providers/ai"},"description":{"name":"description","type":"\u0007","is_mandatory":true,"title":"Explanation of what the prompt does or when to use it","provider":"go.mondoo.com/cnquery/providers/ai"},"name":{"name":"name","type":"\u0007","is_mandatory":true,"title":"Unique prompt name used to request it","provider":"go.mondoo.com/cnquery/providers/ai"},"title":{"name":"title","type":"\u0007","is_mandatory":true,"title":"Human-readable display title","desc":"Title shown to users when listing prompts. Empty when the server omits it.","provider":"go.mondoo.com/cnquery/providers/ai"}},"title":"Model Context Protocol prompt","desc":"Reusable prompt template an MCP server offers, keyed by name. Includes an optional display title, a description of what the prompt does or when to use it, and the arguments it accepts to fill in the template.","private":true,"defaults":"name","provider":"go.mondoo.com/cnquery/providers/ai"},"mcp.resource":{"id":"mcp.resource","name":"mcp.resource","fields":{"description":{"name":"description","type":"\u0007","is_mandatory":true,"title":"Explanation of the content the resource provides","provider":"go.mondoo.com/cnquery/providers/ai"},"mimeType":{"name":"mimeType","type":"\u0007","is_mandatory":true,"title":"MIME type of the resource content","desc":"Content type the resource returns (for example text/plain or application/json). Empty when the server does not report one.","provider":"go.mondoo.com/cnquery/providers/ai"},"name":{"name":"name","type":"\u0007","is_mandatory":true,"title":"Unique resource name used to reference it","provider":"go.mondoo.com/cnquery/providers/ai"},"title":{"name":"title","type":"\u0007","is_mandatory":true,"title":"Human-readable display title","desc":"Title shown to users when listing resources. Empty when the server omits it.","provider":"go.mondoo.com/cnquery/providers/ai"},"uri":{"name":"uri","type":"\u0007","is_mandatory":true,"title":"URI that addresses and retrieves the resource","desc":"Server-defined URI a model uses to read the resource (for example file:///config or a custom scheme). Empty when the server omits it.","provider":"go.mondoo.com/cnquery/providers/ai"}},"title":"Model Context Protocol resource","desc":"Data resource an MCP server makes available as context for a model, keyed by name (for example mcp.resources.where(name == \"config\")). Carries the URI that addresses it, a display title, a description of the content it provides, and the MIME type of that content. Useful for auditing what server-side data a model can pull in as context.","private":true,"defaults":"uri name","provider":"go.mondoo.com/cnquery/providers/ai"},"mcp.resourceTemplate":{"id":"mcp.resourceTemplate","name":"mcp.resourceTemplate","fields":{"description":{"name":"description","type":"\u0007","is_mandatory":true,"title":"Explanation of the resources the template generates","provider":"go.mondoo.com/cnquery/providers/ai"},"name":{"name":"name","type":"\u0007","is_mandatory":true,"title":"Unique resource template name used to reference it","provider":"go.mondoo.com/cnquery/providers/ai"},"title":{"name":"title","type":"\u0007","is_mandatory":true,"title":"Human-readable display title","desc":"Title shown to users when listing resource templates. Empty when the server omits it.","provider":"go.mondoo.com/cnquery/providers/ai"}},"title":"Model Context Protocol resource template","desc":"URI template for addressing a family of parameterized server resources, keyed by name. Carries a display title and a description of the resources the template generates. Useful for understanding which dynamic, argument-addressed resources a model can request.","private":true,"defaults":"name","provider":"go.mondoo.com/cnquery/providers/ai"},"mcp.tool":{"id":"mcp.tool","name":"mcp.tool","fields":{"annotations":{"name":"annotations","type":"\n","is_mandatory":true,"title":"Behavioral hints about the tool","desc":"Annotation dict of server-declared hints: readOnlyHint (the tool does not modify its environment), destructiveHint (it may perform destructive updates, meaningful only when not read-only), idempotentHint (repeated calls with the same arguments have no additional effect), and openWorldHint (it may interact with an open world of external entities such as the web), plus an optional title. These are advisory hints set by the server, not verified guarantees, so do not rely on them alone for security decisions. Useful for spotting tools that can change state or reach external systems.","provider":"go.mondoo.com/cnquery/providers/ai"},"description":{"name":"description","type":"\u0007","is_mandatory":true,"title":"Human-readable explanation of what the tool does","desc":"Description the server provides to help a model decide when to call the tool. Empty when the server omits it.","provider":"go.mondoo.com/cnquery/providers/ai"},"inputSchema":{"name":"inputSchema","type":"\u001bmcp.toolInputSchema","is_mandatory":true,"title":"Schema describing the arguments the tool accepts","provider":"go.mondoo.com/cnquery/providers/ai"},"name":{"name":"name","type":"\u0007","is_mandatory":true,"title":"Unique tool name used to invoke it","provider":"go.mondoo.com/cnquery/providers/ai"}},"title":"Model Context Protocol tool","desc":"Single tool an MCP server exposes for a model to call, keyed by name (for example mcp.tools.where(name == \"search\")). Fields cover the human-readable description shown to the model, server-declared behavioral annotations, and the input schema describing the arguments the tool accepts. Useful for auditing which capabilities a server grants and flagging tools that can modify state or reach external systems before allowing a model to invoke them.","defaults":"name","provider":"go.mondoo.com/cnquery/providers/ai"},"mcp.toolInputSchema":{"id":"mcp.toolInputSchema","name":"mcp.toolInputSchema","fields":{"properties":{"name":"properties","type":"\n","is_mandatory":true,"title":"Per-argument schema definitions keyed by argument name","desc":"JSON Schema fragment for each accepted argument (its type, description, constraints), keyed by the argument name.","provider":"go.mondoo.com/cnquery/providers/ai"},"required":{"name":"required","type":"\u0019\u0007","is_mandatory":true,"title":"Names of the arguments that must be supplied","desc":"Argument names the caller is required to provide; arguments not listed here are optional. Empty when all arguments are optional.","provider":"go.mondoo.com/cnquery/providers/ai"},"type":{"name":"type","type":"\u0007","is_mandatory":true,"title":"Top-level JSON Schema type, typically \"object\"","provider":"go.mondoo.com/cnquery/providers/ai"}},"title":"Model Context Protocol tool input schema","desc":"JSON Schema describing the arguments a tool accepts. The type is the top-level schema type (typically \"object\"), properties holds the per-argument schema definitions keyed by argument name, and required lists the argument names that must be supplied.","private":true,"defaults":"type properties","provider":"go.mondoo.com/cnquery/providers/ai"},"pii":{"id":"pii","name":"pii","fields":{"categories":{"name":"categories","type":"\u0019\u0007","is_mandatory":true,"title":"Named-entity types to detect","desc":"Restricts the named-entity results to the given types; when empty, all recognized named-entity types are returned. Recognized values are PERSON, LOCATION, and ORGANIZATION. This filter applies only to the named-entity results; credit-card matches (CREDIT_CARD) are always included regardless of this list.","provider":"go.mondoo.com/cnquery/providers/ai"},"input":{"name":"input","type":"\u0007","is_mandatory":true,"title":"Text to scan for personal identifiable information","provider":"go.mondoo.com/cnquery/providers/ai"},"results":{"name":"results","type":"\u0019\n","title":"Detected personal data matches","desc":"One entry per match, each holding entity (the matched text), type (one of PERSON, LOCATION, ORGANIZATION, or CREDIT_CARD), and score (model confidence from 0 to 1). Named-entity matches are reported per token without span aggregation, so a multi-word name such as \"David Johnson\" can appear as more than one entry. Credit-card matches come from a regular-expression pattern check (candidate 13 to 19 digit sequences with common issuer prefixes, no Luhn checksum applied in this path) and always score 1. Empty when the input is empty or nothing is detected.","provider":"go.mondoo.com/cnquery/providers/ai"}},"init":{"args":[{"name":"input","type":"\u0007"}]},"title":"Personal identifiable information detection","desc":"Personal data found in a block of text, using a named-entity recognition model (dslim/bert-base-NER, trained on CoNLL-2003) together with a regular-expression credit-card matcher. Select the text with pii(input: \"...\"), optionally narrow the named-entity types with categories, and read results for the matches. The model recognizes person, location, and organization names (its miscellaneous entity class is dropped as too unspecific), and the pattern matcher flags candidate credit-card numbers. Useful for auditing prompts, logs, or documents for leaked personal data before they reach a model or are stored.","provider":"go.mondoo.com/cnquery/providers/ai"},"prompt":{"id":"prompt","fields":{"injection":{"name":"injection","type":"\u001bprompt.injection","title":"Prompt injection detection","desc":"Prompt-injection attempts found in a block of text, using a binary classification model (protectai/deberta-v3-base-prompt-injection-v2) that labels text as safe or injection. Select the text with prompt.injection(input: \"...\") and read results. The input is split into chunks (by line and whitespace, then by length, to stay within the model's 512-token limit) and each chunk is classified independently. This model targets prompt-injection attacks only, does not detect jailbreaks, and is known to produce false positives on legitimate system prompts, so treat matches on trusted content with care. Useful for screening untrusted input before it is passed to a model.","provider":"go.mondoo.com/cnquery/providers/ai","is_implicit_resource":true}},"is_extension":true},"prompt.injection":{"id":"prompt.injection","name":"prompt.injection","fields":{"input":{"name":"input","type":"\u0007","is_mandatory":true,"title":"Text to scan for prompt injection","provider":"go.mondoo.com/cnquery/providers/ai"},"results":{"name":"results","type":"\u0019\n","title":"Detected prompt-injection matches","desc":"One entry per chunk whose top label is injection, each holding entity (the full original input text), type (always PROMPT_INJECTION), and score (the injection-class confidence from 0 to 1). Empty when the input is empty or no chunk is classified as an injection.","provider":"go.mondoo.com/cnquery/providers/ai"}},"init":{"args":[{"name":"input","type":"\u0007"}]},"title":"Prompt injection detection","desc":"Prompt-injection attempts found in a block of text, using a binary classification model (protectai/deberta-v3-base-prompt-injection-v2) that labels text as safe or injection. Select the text with prompt.injection(input: \"...\") and read results. The input is split into chunks (by line and whitespace, then by length, to stay within the model's 512-token limit) and each chunk is classified independently. This model targets prompt-injection attacks only, does not detect jailbreaks, and is known to produce false positives on legitimate system prompts, so treat matches on trusted content with care. Useful for screening untrusted input before it is passed to a model.","provider":"go.mondoo.com/cnquery/providers/ai"},"transformers":{"id":"transformers","fields":{"pipeline":{"name":"pipeline","type":"\u001btransformers.pipeline","title":"Transformers pipeline","desc":"Run of a Hugging Face transformers pipeline over one or more text inputs, for classifying text with an arbitrary model. Set task, model, and inputs, then read results. Only the text-classification task is implemented; any other task value returns an error. Useful for applying a custom or third-party classifier (toxicity, sentiment, topic, and so on) to text as part of an audit.","provider":"go.mondoo.com/cnquery/providers/ai","is_implicit_resource":true}},"is_extension":true},"transformers.pipeline":{"id":"transformers.pipeline","name":"transformers.pipeline","fields":{"inputs":{"name":"inputs","type":"\u0019\u0007","is_mandatory":true,"title":"Text inputs to run through the pipeline","desc":"Each string is classified independently and produces one result.","provider":"go.mondoo.com/cnquery/providers/ai"},"model":{"name":"model","type":"\u0007","is_mandatory":true,"title":"Hugging Face model identifier to run","desc":"Model repository name on the Hugging Face Hub (for example \"distilbert-base-uncased-finetuned-sst-2-english\"). The model is downloaded and cached locally on first use.","provider":"go.mondoo.com/cnquery/providers/ai"},"name":{"name":"name","type":"\u0007","is_mandatory":true,"title":"Pipeline name","provider":"go.mondoo.com/cnquery/providers/ai"},"onnxFilePath":{"name":"onnxFilePath","type":"\u0007","is_mandatory":true,"title":"Path to the ONNX model file within the model repository","desc":"Optional; set when the model must be loaded from a specific ONNX file rather than the repository default.","provider":"go.mondoo.com/cnquery/providers/ai"},"results":{"name":"results","type":"\u0019\n","title":"Classification results","desc":"One entry per input, each holding label (the single highest-scoring class predicted by the model, chosen by argmax over a softmax), score (that class's confidence from 0 to 1), and input (the original text).","provider":"go.mondoo.com/cnquery/providers/ai"},"task":{"name":"task","type":"\u0007","is_mandatory":true,"title":"Pipeline task to run","desc":"The transformers task, for example \"text-generation\" or \"text-classification\". Only \"text-classification\" is implemented; any other value returns an error.","provider":"go.mondoo.com/cnquery/providers/ai"}},"title":"Transformers pipeline","desc":"Run of a Hugging Face transformers pipeline over one or more text inputs, for classifying text with an arbitrary model. Set task, model, and inputs, then read results. Only the text-classification task is implemented; any other task value returns an error. Useful for applying a custom or third-party classifier (toxicity, sentiment, topic, and so on) to text as part of an audit.","provider":"go.mondoo.com/cnquery/providers/ai"}}}