Schema Guide

📦 v1.3.1 (Stable)

Archived Version

This is the v1.3.1 documentation. For the latest features, see v1.4 docs →

Human-readable guide to PromptPack entities and their properties. For the auto-generated technical reference, see Schema Reference.

Root Properties

The root object of every PromptPack file. Required fields are id, name, version, template_engine, and prompts.

Field	Type	Required	Description
$schema	string	No	JSON Schema reference for validation and IDE support. Default: https://promptpack.org/schema/v1/promptpack.schema.json
id	string	Yes	Unique identifier for the pack. Lowercase with hyphens only. Pattern: ^[a-z][a-z0-9-]*$ (1--100 chars).
name	string	Yes	Human-readable display name for the pack (1--200 chars).
version	string	Yes	Pack version following Semantic Versioning 2.0.0. Optional v prefix. Examples: "1.0.0", "v2.1.3".
description	string	No	Detailed description of the pack's purpose. Supports markdown (max 5000 chars).
template_engine	TemplateEngine	Yes	Template engine configuration shared across all prompts.
prompts	object<string, Prompt>	Yes	Map of task type keys to prompt definitions. Must contain at least one entry.
fragments	object<string, string>	No	Shared template fragments. Keys are fragment names, values are fragment content strings.
tools	object<string, Tool>	No	Tool definitions that prompts can reference. Keys are tool names, values are tool specs.
metadata	Metadata	No	Optional pack-level metadata for categorization and discovery.
compilation	Compilation	No	Information about when and how the pack was compiled. Generated by packc.
evals	Eval[]	No	Pack-level eval definitions. Cross-cutting quality checks that apply to all prompts. (v1.2+)
workflow	WorkflowConfig	No	State-machine workflow over the pack's prompts with event-driven transitions. (v1.3+)
agents	AgentsConfig	No	Agent configuration mapping prompts to A2A-compatible agent definitions. (v1.3+)
skills	SkillSource[]	No	Skill sources for progressive-disclosure knowledge loading. (v1.3.1+)

Collections are keyed maps, not arrays

prompts, fragments, and tools are all objects (keyed maps), not arrays. Each key serves as the identifier for the entry. For example, prompts maps task type strings like "support" or "billing" to their Prompt definitions.

Minimal Example

{
  "$schema": "https://promptpack.org/schema/v1/promptpack.schema.json",
  "id": "my-pack",
  "name": "My Pack",
  "version": "1.0.0",
  "template_engine": {
    "version": "v1",
    "syntax": "{{variable}}"
  },
  "prompts": {
    "greeting": {
      "id": "greeting",
      "name": "Greeter",
      "version": "1.0.0",
      "system_template": "You are a friendly assistant for {{company}}."
    }
  }
}

---

Template Engine

Configuration for how variables are substituted and fragments are resolved across all prompts.

Field	Type	Required	Description
version	string	Yes	Template engine version (e.g., "v1").
syntax	string	Yes	Variable substitution syntax pattern (e.g., "{{variable}}").
features	string[]	No	Supported template features. Allowed values: "basic_substitution", "fragments", "conditionals", "loops", "filters".

"template_engine": {
  "version": "v1",
  "syntax": "{{variable}}",
  "features": ["basic_substitution", "fragments"]
}

---

Prompt

A single prompt configuration within a pack. Each prompt represents a specific task type (e.g., "support", "sales") with its own template, variables, tools, and validation rules. Prompts can evolve independently with their own version numbers.

Field	Type	Required	Description
id	string	Yes	Unique identifier, typically matching the map key. Pattern: ^[a-z][a-z0-9_-]*$.
name	string	Yes	Human-readable name.
version	string	Yes	Prompt version following Semantic Versioning, independent from the pack version.
system_template	string	Yes	The system prompt template. Use template syntax (e.g., {{variable}}) for variable substitution.
description	string	No	Detailed description of the prompt's purpose and behavior.
variables	Variable[]	No	Variable definitions for template placeholders.
tools	string[]	No	List of tool names this prompt can use. Tools must be defined in the pack-level tools map.
tool_policy	ToolPolicy	No	Policy governing how tools can be used.
pipeline	PipelineConfig	No	Pipeline configuration defining processing stages and middleware.
parameters	Parameters	No	LLM generation parameters (temperature, max_tokens, etc.).
validators	Validator[]	No	Validation rules (guardrails) applied to LLM responses.
tested_models	TestedModel[]	No	Model testing results documenting performance across different models.
model_overrides	object<string, ModelOverride>	No	Model-specific template modifications. Keys are model names (e.g., "claude-3-opus", "gpt-4").
evals	Eval[]	No	Prompt-level eval definitions. Override pack-level evals by id. (v1.2+)
media	MediaConfig	No	Multimodal content configuration. Defines supported media types and constraints. (v1.1+)

"prompts": {
  "support": {
    "id": "support",
    "name": "Support Bot",
    "version": "1.0.0",
    "system_template": "You are a {{role}} assistant for {{company}}.\n\nHelp resolve their issue.",
    "variables": [
      { "name": "role", "type": "string", "required": true, "example": "support agent" },
      { "name": "company", "type": "string", "required": true, "default": "TechCo" }
    ],
    "tools": ["lookup_order", "create_ticket"],
    "parameters": { "temperature": 0.7, "max_tokens": 1500 }
  }
}

---

Variable

A template variable definition with type information and validation rules.

Field	Type	Required	Description
name	string	Yes	Variable name used in templates (e.g., {{name}}). Pattern: ^[a-zA-Z_][a-zA-Z0-9_]*$.
type	string	Yes	Data type. One of: "string", "number", "boolean", "object", "array".
required	boolean	Yes	Whether this variable must be provided at runtime.
default	any	No	Default value when the variable is not provided.
description	string	No	Human-readable description of the variable's purpose.
example	any	No	Example value showing expected format and content.
validation	Validation	No	Validation rules applied to the variable value at runtime.

Validation

Rules applied to variable values at runtime.

Field	Type	Description
pattern	string	Regular expression pattern (for string types).
min_length	integer	Minimum string length. Minimum value: 0.
max_length	integer	Maximum string length. Minimum value: 1.
minimum	number	Minimum numeric value (for number types).
maximum	number	Maximum numeric value (for number types).
enum	any[]	List of allowed values.

{
  "name": "priority",
  "type": "string",
  "required": true,
  "description": "Support ticket priority level",
  "validation": {
    "enum": ["low", "medium", "high", "urgent"]
  }
}

---

Tool

A tool definition following the function calling convention. Tools enable the LLM to call external functions. Tools are defined at the pack level and referenced by name in each prompt's tools array.

Field	Type	Required	Description
name	string	Yes	Tool name. Pattern: ^[a-zA-Z_][a-zA-Z0-9_]*$.
description	string	Yes	What the tool does. The LLM uses this to decide when to call it.
parameters	object	No	JSON Schema object defining the tool's input parameters (see below).

Tool Parameters (JSON Schema Format)

Tool parameters use standard JSON Schema format. The parameters object must have type: "object" with a properties map and an optional required array.

Field	Type	Required	Description
type	string	Yes	Must be "object".
properties	object	Yes	Map of parameter names to their JSON Schema definitions.
required	string[]	No	List of required parameter names.

"tools": {
  "create_ticket": {
    "name": "create_ticket",
    "description": "Create a support ticket with title, description, and priority",
    "parameters": {
      "type": "object",
      "properties": {
        "title": {
          "type": "string",
          "description": "Ticket title"
        },
        "priority": {
          "type": "string",
          "enum": ["low", "medium", "high", "urgent"]
        }
      },
      "required": ["title"]
    }
  }
}

---

Tool Policy

Governance policy for tool usage. Controls when and how tools can be called by the LLM.

Field	Type	Required	Description
tool_choice	string	No	"auto" (LLM decides), "required" (must use tools), or "none" (tools disabled). Default: "auto".
max_rounds	integer	No	Maximum number of LLM-tool-LLM cycles per turn. Minimum: 1. Default: 5.
max_tool_calls_per_turn	integer	No	Maximum tool calls allowed in a single turn. Minimum: 1. Default: 10.
blocklist	string[]	No	Tool names that are not allowed for this prompt (overrides the tools list).

---

Parameters

LLM generation parameters controlling the model's behavior and output characteristics.

Field	Type	Required	Description
temperature	number	No	Sampling temperature (0--2). Higher values increase randomness.
max_tokens	integer	No	Maximum number of tokens to generate. Minimum: 1.
top_p	number	No	Nucleus sampling parameter (0--1). Alternative to temperature.
top_k	integer or null	No	Top-k sampling. null means no limit. Minimum: 1.
frequency_penalty	number	No	Penalty for token frequency (-2 to 2). Positive values reduce repetition.
presence_penalty	number	No	Penalty for token presence (-2 to 2). Positive values encourage new topics.

"parameters": {
  "temperature": 0.7,
  "max_tokens": 1500,
  "top_p": 0.9
}

---

Validator

A validation rule (guardrail) applied to LLM responses.

Field	Type	Required	Description
type	string	Yes	The validator type that determines how validation is performed. Not an enum — runtimes define and register their own types. Examples: "banned_words", "max_length", "length", "max_sentences", "regex_match", "sentiment", "custom".
enabled	boolean	Yes	Whether this validator is active.
fail_on_violation	boolean	No	If true, violations cause an error. Default: false.
params	object	No	Validator-specific parameters (e.g., word lists, character limits).

"validators": [
  {
    "type": "banned_words",
    "enabled": true,
    "fail_on_violation": true,
    "params": {
      "words": ["impossible", "can't help"]
    }
  },
  {
    "type": "pii_detection",
    "enabled": true,
    "fail_on_violation": true
  }
]

---

Tested Model

Documents which models have been tested with a prompt and their performance metrics.

Field	Type	Required	Description
provider	string	Yes	LLM provider name (e.g., "openai", "anthropic").
model	string	Yes	Specific model identifier (e.g., "gpt-4", "claude-3-opus").
date	string	Yes	Date tested in YYYY-MM-DD format.
success_rate	number	No	Success rate from test runs (0--1).
avg_tokens	number	No	Average tokens used per response.
avg_cost	number	No	Average cost per execution in USD.
avg_latency_ms	number	No	Average response latency in milliseconds.
notes	string	No	Additional observations about model performance.

---

Model Override

Model-specific template modifications. Allows customizing prompts for specific models without changing the base template.

Field	Type	Required	Description
system_template_prefix	string	No	Text prepended to the system template for this model.
system_template_suffix	string	No	Text appended to the system template for this model.
system_template	string	No	Complete replacement system template (overrides the base template entirely).
parameters	Parameters	No	Model-specific parameter overrides.

"model_overrides": {
  "claude-3-opus": {
    "system_template_prefix": "<thinking>\n",
    "parameters": { "temperature": 0.5 }
  }
}

---

Pipeline Config

Pipeline configuration defining processing stages and middleware.

Field	Type	Required	Description
stages	string[]	Yes	Ordered list of pipeline stages (e.g., ["template", "provider", "validator"]).
middleware	MiddlewareConfig[]	No	Middleware components applied in order.

Middleware Config

Field	Type	Required	Description
type	string	Yes	Middleware type identifier (e.g., "template", "provider", "validator").
config	object	No	Type-specific configuration.

---

Metadata

Optional pack-level metadata for categorization and discovery.

Field	Type	Required	Description
domain	string	No	Domain or category (e.g., "customer-service", "healthcare").
language	string	No	Primary language code (ISO 639-1, e.g., "en"). Pattern: ^[a-z]{2}$.
tags	string[]	No	Tags for categorization and discovery.
cost_estimate	object	No	Cost estimation with min_cost_usd, max_cost_usd, and avg_cost_usd.

---

Compilation

Compiler-generated information about when and how the pack was built.

Field	Type	Required	Description
compiled_with	string	Yes	Version of the packc compiler (e.g., "packc-v0.1.0").
created_at	string	Yes	ISO 8601 timestamp when the pack was compiled.
schema	string	Yes	Pack format schema version (e.g., "v1").
source	string	No	Source configuration file path.

---

Evals (v1.2+)

Evals are automated quality checks on LLM outputs. Unlike validators (which run inline and can block responses), evals run asynchronously and produce scores or metrics. Evals can be defined at both pack level (cross-cutting) and prompt level (prompt-specific). Prompt-level evals with the same id override pack-level evals.

Eval

Field	Type	Required	Description
id	string	Yes	Unique identifier for this eval within its scope.
type	string	Yes	Assertion type determining how the eval runs. Not an enum — runtimes register their own types (e.g., "contains", "regex", "json_valid", "llm_judge").
trigger	string	Yes	When this eval fires. One of: "every_turn", "on_session_complete", "sample_turns", "sample_sessions".
description	string	No	Human-readable description of what this eval measures.
enabled	boolean	No	Whether this eval is active. Default: true.
sample_percentage	number	No	Percentage of turns/sessions to sample (0–100). Only used with sample_turns and sample_sessions triggers. Default: 5.
params	object	No	Type-specific configuration. Structure depends on the eval type.
metric	MetricDef	No	Prometheus-style metric declaration for exposing eval results.

Metric Def

Field	Type	Required	Description
name	string	Yes	Metric name following Prometheus conventions (snake_case). Pattern: ^[a-zA-Z_:][a-zA-Z0-9_:]*$.
type	string	Yes	Metric type. One of: "gauge", "counter", "histogram", "boolean".
range	object	No	Optional value bounds with min and/or max fields.

The metric object uses additionalProperties: true, so runtimes can attach extra fields (e.g., labels, help, buckets).

"evals": [
  {
    "id": "json_format",
    "type": "json_valid",
    "trigger": "every_turn",
    "description": "Verify the assistant always returns valid JSON",
    "metric": {
      "name": "promptpack_json_valid",
      "type": "boolean"
    }
  },
  {
    "id": "tone-check",
    "type": "llm_judge",
    "trigger": "sample_turns",
    "sample_percentage": 10,
    "params": {
      "judge_prompt": "Rate the response tone on a 1-5 scale for professionalism.",
      "model": "gpt-4o",
      "passing_score": 4
    },
    "metric": {
      "name": "promptpack_tone_score",
      "type": "gauge",
      "range": { "min": 1, "max": 5 }
    }
  }
]

Validators vs Evals

Both sit on the quality spectrum: validators run inline on every response and can block output (fail_on_violation), while evals run asynchronously and produce scores/metrics without blocking. Use validators for hard guardrails, evals for quality measurement and monitoring.

---

Fragments

Fragments are shared, reusable template text blocks defined at the pack level. They are simple string values keyed by name.

"fragments": {
  "customer_context": "Customer: {{customer_name}}\nAccount Type: {{account_type}}",
  "greeting": "Hello! How can I help you today?",
  "escalation_notice": "I'm going to connect you with a specialist."
}

Prompts reference fragments in their system_template using template syntax: {{fragments.customer_context}}.

---

Multimodal Support (v1.1+)

PromptPack v1.1 adds multimodal content support through media configuration on individual prompts.

Media Config

Field	Type	Required	Description
enabled	boolean	Yes	Whether multimodal content is enabled for this prompt.
supported_types	string[]	No	Supported media types (e.g., "image", "audio", "video", "document"). Custom types allowed.
image	ImageConfig	No	Image-specific constraints.
audio	AudioConfig	No	Audio-specific constraints.
video	VideoConfig	No	Video-specific constraints.
document	DocumentConfig	No	Document-specific constraints.
examples	MultimodalExample[]	No	Example multimodal messages.

Image Config

Field	Type	Description
max_size_mb	integer	Maximum file size in MB.
allowed_formats	string[]	Allowed formats: "jpeg", "jpg", "png", "webp", "gif", "bmp".
default_detail	string	Detail level: "low", "high", or "auto" (default: "auto").
require_caption	boolean	Whether captions are required (default: false).
max_images_per_msg	integer	Maximum images per message.

Audio Config

Field	Type	Description
max_size_mb	integer	Maximum file size in MB.
allowed_formats	string[]	List of allowed audio format strings (open list, e.g. "mp3", "wav", "ogg", "webm").
max_duration_sec	integer	Maximum duration in seconds.
require_metadata	boolean	Whether metadata is required (default: false).

Video Config

Field	Type	Description
max_size_mb	integer	Maximum file size in MB.
allowed_formats	string[]	Allowed formats: "mp4", "webm", "mov", "avi", "mkv".
max_duration_sec	integer	Maximum duration in seconds.
require_metadata	boolean	Whether metadata is required (default: false).

Document Config

Field	Type	Description
max_size_mb	integer	Maximum file size in MB.
allowed_formats	string[]	Allowed formats (e.g., "pdf", "docx", "csv").
max_pages	integer	Maximum pages/sheets.
require_metadata	boolean	Whether metadata is required (default: false).
extraction_mode	string	Content extraction: "text", "structured", or "raw" (default: "text").

Generic Media Type Config

For custom media types not covered by the specific configs above.

Field	Type	Description
max_size_mb	integer	Maximum file size in MB.
allowed_formats	string[]	Allowed file formats/extensions.
require_metadata	boolean	Whether metadata is required (default: false).
validation_params	object	Custom validation parameters specific to this media type.

Multimodal Example

Field	Type	Required	Description
name	string	Yes	Name identifying this example.
description	string	No	What this example demonstrates.
role	string	Yes	Message role: "user", "assistant", or "system".
parts	ContentPart[]	Yes	Message content parts (text and/or media).

Content Part

Field	Type	Required	Description
type	string	Yes	Part type (e.g., "text", "image", "audio").
text	string	No	Text content (when type is "text").
media	MediaReference	No	Media reference (when type is a media type).

Media Reference

Field	Type	Required	Description
mime_type	string	Yes	MIME type (e.g., "image/jpeg", "audio/mp3").
file_path	string	No	Path to media file.
url	string	No	URL to media file.
base64	string	No	Base64-encoded media data.
detail	string	No	Detail level for images: "low", "high", or "auto".
caption	string	No	Caption or description for the media.

"media": {
  "enabled": true,
  "supported_types": ["image"],
  "image": {
    "max_size_mb": 20,
    "allowed_formats": ["jpeg", "png", "webp"],
    "default_detail": "high",
    "max_images_per_msg": 5
  }
}

---

Workflow (v1.3+)

PromptPack v1.3 adds a state-machine workflow over the pack's prompts. Each state references a prompt key and declares event-driven transitions to other states.

WorkflowConfig

Field	Type	Required	Description
version	integer	Yes	Workflow schema version. Use 1 for the current stable format.
entry	string	Yes	Name of the initial state. Must match a key in the states object.
states	object<string, WorkflowState>	Yes	Map of state name to state definition. Must contain at least one entry.
engine	object	No	Optional runtime engine hints for workflow execution (e.g., timeout, concurrency settings).

WorkflowState

Field	Type	Required	Description
prompt_task	string	Yes	Reference to a prompt key defined in the pack's prompts object.
description	string	No	Human-readable description of this state's purpose.
on_event	object<string, string>	Yes	Map of event name to target state name. When the named event fires, the workflow transitions to the target state.
persistence	string	No	Whether conversation context is kept (persistent) or reset (transient) on entry.
orchestration	string	No	How this state is orchestrated: internal (runtime manages), external (caller manages), or hybrid.
skills	string	No	Skill filter for this state. A path scoping which skills are available, or "none" to disable skills. (v1.3.1+)

"workflow": {
  "version": 1,
  "entry": "triage",
  "states": {
    "triage": {
      "prompt_task": "triage",
      "description": "Route incoming requests to the appropriate specialist",
      "on_event": {
        "billing": "billing_support",
        "technical": "tech_support",
        "resolved": "closing"
      }
    },
    "billing_support": {
      "prompt_task": "billing",
      "on_event": { "resolved": "closing", "escalate": "human_handoff" },
      "persistence": "persistent"
    },
    "tech_support": {
      "prompt_task": "technical",
      "on_event": { "resolved": "closing", "escalate": "human_handoff" },
      "persistence": "persistent"
    },
    "closing": {
      "prompt_task": "closing",
      "on_event": {},
      "orchestration": "internal"
    },
    "human_handoff": {
      "prompt_task": "handoff",
      "on_event": {},
      "orchestration": "external"
    }
  }
}

---

Agents (v1.3+)

PromptPack v1.3 adds agent definitions that map prompts to A2A (Agent-to-Agent) compatible agent cards. This enables multi-agent orchestration via the A2A protocol.

AgentsConfig

Field	Type	Required	Description
entry	string	Yes	Prompt key of the entry agent — the default agent that receives incoming requests.
members	object<string, AgentDef>	Yes	Map of prompt key to agent definition. Each key must match a prompt defined in the pack's prompts object. Must contain at least one entry.

AgentDef

Field	Type	Required	Description
description	string	No	Agent description published in the A2A Agent Card. Overrides the prompt's description if set.
tags	string[]	No	Discovery tags for the agent, used by A2A registries and routers.
input_modes	string[]	No	MIME types the agent accepts as input. Defaults to ["text/plain"].
output_modes	string[]	No	MIME types the agent can produce as output. Defaults to ["text/plain"].

"agents": {
  "entry": "triage",
  "members": {
    "triage": {
      "description": "Routes customer requests to the right specialist",
      "tags": ["router", "customer-service"],
      "input_modes": ["text/plain"],
      "output_modes": ["text/plain"]
    },
    "billing": {
      "description": "Handles billing inquiries and payment issues",
      "tags": ["billing", "payments"],
      "input_modes": ["text/plain"],
      "output_modes": ["text/plain", "application/json"]
    },
    "technical": {
      "description": "Provides technical troubleshooting assistance",
      "tags": ["support", "technical"]
    }
  }
}

Workflow + Agents

workflow and agents are independent features — you can use either or both. When used together, the workflow drives state transitions while agent definitions provide A2A discoverability metadata for each prompt.

---

Skills (v1.3.1+)

PromptPack v1.3.1 adds skills for progressive-disclosure knowledge loading. Skills are modular knowledge sources that agents load on demand, keeping system templates lean while providing access to deep domain expertise.

SkillSource

Each entry in the top-level skills array is one of three forms:

Form	Type	Description
String	string	Path to a skill directory/file or a package reference (e.g., "./skills/billing", "@acme/support-skills").
SkillPathSource	SkillPathSource	Path object with optional preload flag.
InlineSkill	InlineSkill	Skill defined directly in the pack.

SkillPathSource

Field	Type	Required	Description
path	string	Yes	Path to a skill directory, file, or package reference.
preload	boolean	No	If true, load eagerly at pack initialization. Default: false.

InlineSkill

Field	Type	Required	Description
name	string	Yes	Human-readable name for this skill.
description	string	Yes	Brief description of what this skill provides.
instructions	string	Yes	The skill's instructions or knowledge content. Loaded into the agent's context when activated.

"skills": [
  "./skills/billing",
  { "path": "./skills/compliance", "preload": true },
  {
    "name": "escalation-protocol",
    "description": "Steps for escalating unresolved customer issues",
    "instructions": "When a customer issue cannot be resolved within 3 exchanges:\n1. Acknowledge the complexity\n2. Collect case details\n3. Create an escalation ticket\n4. Provide the ticket reference to the customer"
  }
]

Skills + Workflow

When a WorkflowState declares a skills field, it scopes which skills are available in that state. Use "none" to disable skills for a state. Without a skills field, all pack-level skills are available.

---

Data Types

Supported Variable Types

• string -- Text data
• number -- Numeric values (integers and floats)
• boolean -- True/false values
• array -- Ordered lists of values
• object -- Key-value maps

Template Variables

Variables in templates use the syntax defined in template_engine.syntax. With the default {{variable}} syntax:

{{variable_name}}

Fragments are referenced similarly:

{{fragments.fragment_name}}