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This guide shows how to get the most out of Pria with precise prompts, complete context via IP Vault, verifiable outputs with Agent Details, and repeatable workflows using Assistants. It aligns with Praxis AI’s operating model and links to relevant documentation where applicable. To unlock the full potential of Praxis AI’s Pria and ensure optimal, precise, and efficient interactions, integrate these ten best practices into your workflow. By doing so, you can significantly enhance the quality of responses, streamline research, and effectively manage your AI-driven tasks.

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At a glance

1- Be specific

Craft precise, bounded prompts with clear deliverables, tone, and constraints.

2- Use IP Vault for websites

Scrape full sites to give Pria clean, complete context instead of noisy partial HTML.

3- Verify with Agent Details

See which agent ran, sources used, success status, and returned data.

4- Manage conversations

Create and choose the right conversation to preserve context and retrieve history.

5- Set perspective

Tell Pria which role to adopt for audience-aligned output.

6- Create Assistants

Automate multi-step workflows with clear, ordered instructions and error handling.

7- Apply CRISPE

Design robust Assistants with a structured capability and context template.

8- Iterate & validate

Use Agent Details to identify gaps and refine prompts or sources accordingly.

9- Stay organized

Name conversations and Assistants consistently for easy retrieval.

10- Respect governance

Follow data, privacy, and safety rules using IP Vault and RAG over ad-hoc copy-paste.

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1 Be Specific: The power of detailed requests and context

The foundation of effective interaction with Pria lies in the specificity and depth of your prompts. A well-crafted request, rich in detail and relevant context, directly correlates with the quality and accuracy of the AI’s response. Specificity directly improves precision and reduces rework.
Think of your prompt as a detailed instruction manual for Pria. The more precise you are, the better the results.

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Why Specificity Matters

Avoid vague or ambiguous language. Clearly articulate what you need, including any specific parameters, desired formats, or limitations. A detailed request helps Pria understand exactly what you’re looking for and deliver accurate, relevant responses.

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Building Specific Prompts

1

State the objective and audience

What should be produced and for whom (e.g., teachers vs. executives). Define the purpose and target audience clearly.
2

Constrain format and scope

Word count, headings, components, style, and what to exclude. Set boundaries for length, structure, and content.
3

Provide source context

Attach RAG/IP Vault content or quote key excerpts. Give Pria access to the information sources it should use.
4

Define success criteria

Checks, tests, or acceptance conditions. Explain how to evaluate if the output meets your needs.

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Example: Generic vs. Specific

Generic: “Write about marketing”Specific: “Write a 500-word blog post on the latest trends in digital marketing for small businesses, focusing on SEO strategies and social media engagement, in a conversational yet authoritative tone.”

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Complete Example Prompt

Objective: Draft a 500–600 word announcement for small businesses about Q1 SEO trends.
Audience & tone: Conversational yet authoritative; non-technical.
Format: 4 sections (Overview, Trend 1, Trend 2, Actions); include 3 actionable bullets.
Constraints: Cite any stats inline; avoid jargon like "synergy"; no images.
Sources: Use my IP Vault document for "AcmeSEO Blog Q1 2025" and my RAG file "Search Trends Notes".
Success: Clear 90-day action plan and linked glossary terms.

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2 Website research via IP Vault: Comprehensive scraping

When gathering information from websites, leverage the IP Vault for comprehensive data acquisition rather than simply asking Pria to “look at this website.” This method offers significant advantages in terms of content depth and cleanliness.

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Why IP Vault?

Full-context capture

Pulls complete site content for deep analysis, not just partial HTML. Utilizing the IP Vault to scrape a site allows you to capture the entire content, providing Pria with the complete context needed for thorough analysis and accurate response generation.

Clean data

Filters out extraneous JS/CSS and delivers structured text. Direct URL reading by Pria typically yields only about 20% of the content, often intermingled with extraneous HTML and JavaScript. Scraping via the IP Vault ensures a much cleaner, more comprehensive dataset.

Repeatable

Documents are reusable across conversations and Assistants. Once scraped, the content can be referenced multiple times without re-scraping.

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The Problem with Direct URL Reading

Direct URL reading by Pria often results in:
  • Only ~20% of actual content captured
  • Content mixed with HTML, JavaScript, and CSS code
  • Incomplete context for analysis
  • Noisy, unstructured data

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Using IP Vault Effectively

1

Create a site snapshot file

Add the site to IP Vault and complete the scrape. This captures the full website content in a clean, structured format.
2

Name and tag consistently

Use descriptive names like VendorX Docs (2025-10-02) | pricing, api, auth to make documents easy to find and reference.
3

Reference documents explicitly

Tell Pria which file to use by name to ensure it uses the right source.
4

Limit scope as needed

Ask for specific sections to avoid noise and focus on relevant content.
5

Refresh on updates

Re-scrape periodically when content changes to keep your data current.

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Example Usage

Use IP Vault: "Compare pricing tiers from 'VendorX Docs (2025-10-02)' and map features to our needs.
Avoid direct URL reads; use my document only."
This eliminates the limitations often encountered when Pria directly reads URLs and improves Pria’s ability to process and synthesize information effectively.

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3 Agent Details: Unveil process and verification

The “Agent Details” feature is an invaluable tool for understanding how Pria constructs its responses and verifying the integrity of the information provided. Agent Details shows which agent executed, whether it succeeded, which sources were used (RAG, IP Vault, browser), and what data was returned.
This transparency is crucial for assessing the reliability and originality of the AI’s output.

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What Agent Details Reveals

By examining Agent Details, you can discern which sources and methods Pria employed to compile its response. This insight helps you differentiate between information directly retrieved (e.g., from a search in RAG via call_rag or the internet via get_browser) and content that might be inferred or generated by the LLM.Key information includes:
  • Agent identity and version
  • Execution ruration
  • Input parameters used
  • Server label (mcp)
  • Response Text
The details indicate which agent was used, whether it was successful in its operation, and what specific data or output it returned. This allows you to:
  • Verify successful execution
  • Identify error messages and failure points
  • Review source breakdown (RAG sections, IP Vault documents, web fetches)
  • Examine returned artifacts (tables, JSON, files)
Agent Details shows exactly which sources were consulted:
  • RAG documents and specific sections
  • IP Vault files referenced
  • Web searches performed
  • API calls made
This transparency helps you validate that Pria used the correct and most relevant sources.
Use the information in Agent Details to improve your interactions:
  • If sources are missing: Attach or reference the right RAG/IP Vault items
  • If a step failed: Retry with narrower scope or corrected parameters
  • If inference is high: Ask Pria to separate “retrieved facts” vs “model inferences”
  • If output quality is low: Identify which steps succeeded and which need refinement

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Why This Matters

Agent Details helps you identify potential gaps in information retrieval or areas where Pria might have had to “fill in the blanks,” guiding you on when further investigation or clarification might be needed.
Always review Agent Details for critical or high-stakes outputs to ensure the response is built on reliable, verifiable sources rather than model inference.

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4 Manage conversations: Organize context and history

Effective conversation management is essential for maintaining context and preventing information loss within your interactions with Pria. Each new thought or topic should ideally initiate a new conversation.

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Why Conversation Management Matters

Pria’s responses are heavily influenced by the current conversation’s history. Selecting the appropriate conversation ensures that Pria has access to all relevant prior interactions, leading to more coherent and accurate responses.

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Contextual Integrity

Conversations organize your dialogues and maintain the context that Pria uses to generate responses. Proper conversation management ensures:
  • Context Preservation: Pria remembers relevant details from earlier in the conversation
  • Accuracy: Responses build on established context rather than starting fresh
  • Coherence: Multi-turn interactions maintain logical flow and reference earlier points

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Best Practices for Conversation Management

1

Start a new conversation per topic

Prevents cross-topic contamination. Each distinct topic or project should have its own conversation thread.
2

Pick the correct conversation before asking

Ensures relevant history is available. Before asking a question, verify you’re in the right conversation context.
3

Name conversations descriptively

Use clear, specific names like “Mintlify Writer — Pria Best Practices” or “Q4 Marketing Campaign Planning” to make conversations easy to identify and retrieve.
4

Leverage 'Clear selected' to broaden history

Allows Pria to draw across prior threads when appropriate. This broadens Pria’s contextual understanding, allowing it to draw upon a wider range of past interactions.

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Organization and Retrieval

If something “disappears,” check a different conversation thread. Context is scoped per thread by design. If you suspect information has been lost, it might simply be part of a different conversation thread.

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Assistant-Driven Workflows

Conversations are often created in conjunction with Assistants, which are designed to execute specific instructional workflows. Aligning your questions with the correct conversation ensures Pria applies the appropriate Assistant’s logic and context.
Create a naming convention for your conversations that includes the project, date, or Assistant type to make them easier to find later.

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5 Use perspective: Define Pria’s role explicitly

Directing Pria to adopt a specific persona or role can significantly enhance the relevance and tone of its responses. By framing your request with a defined perspective, you guide Pria to generate output that aligns with that particular expertise.

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Why Perspective Matters

Explicitly stating Pria’s desired role ensures the output resonates with the intended audience and purpose. The perspective you set determines:
  • Vocabulary and terminology used
  • Depth and technical level of explanations
  • Tone and communication style
  • Focus and priorities in the response

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Examples of Effective Perspective Setting

Social Media Expert

"As a social media strategist, create a 7-day content plan prioritizing short-form video
for small retailers. Include hooks, CTAs, and platform-specific notes."

AI Engineer

"As an AI engineer, outline a Node service to summarize PDFs using our IP Vault documents.
Include architecture, error handling, and timeouts."

Business Analyst

"As a business analyst, review our Q3 sales data and identify the top 3 trends
impacting revenue. Present findings in executive summary format."

Technical Writer

"As a technical writer, document this API endpoint with clear examples,
parameter descriptions, and common error scenarios."

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Tailored Communication

When you instruct Pria to act as an “AI engineer,” it will leverage its understanding of AI principles and development to “build an app for me that does A, B, and C,” providing solutions and insights relevant to that technical domain.

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Setting Effective Perspectives

State domain, deliverable, constraints, and evaluation criteria in the first message to lock in the perspective. This ensures consistent output aligned with your needs.
Template for perspective setting: 
As a [ROLE], [ACTION] for [AUDIENCE/PURPOSE].
Include [SPECIFIC ELEMENTS].
Use [TONE/STYLE].
Focus on [PRIORITIES].
The perspective you set influences every aspect of Pria’s response, from word choice to structural organization to the depth of technical detail provided.

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6 Create Assistants: Automate and optimize workflows

The ability to create custom Assistants within Praxis AI is a powerful tool for automating repetitive tasks and streamlining complex operational workflows. Developing this skill is a crucial aspect of mastering prompt engineering.

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Why Create Assistants?

Automation

Assistants are designed to follow a defined set of step-by-step instructions, effectively automating routine or multi-stage processes. This frees up your time for more strategic tasks.

Consistency

Structured operational workflows ensure consistency and accuracy in task execution across multiple runs.

Repeatability

Turn reliable processes into repeatable, multi-step runs with consistent quality.

Optimization

Refine and optimize workflows over time based on performance and outcomes.

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Assistant Core Pattern

Assistants turn reliable processes into repeatable, multi-step runs with consistent quality. An Assistant’s instructions define a clear, sequential workflow for the AI to follow.

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Basic Assistant Template

You are the "XXX" assistant and your role is to create YYY by following the step-by-step instructions below carefully:

1- Collect input from user through conversation
2- Analyze the data
3- Generate your response
4- End of job

Error Handling:
A- Not enough or invalid input data: Continue or restart at step 1
B- Off topic: Redirect off topic back to the focus of this assistant

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Key Elements of Effective Assistants

1

Clear role definition

Start by defining what the Assistant is and what it produces.
2

Sequential steps

Break down the workflow into numbered, atomic steps that are easy to follow and verify.
3

Error handling

Define what happens when things go wrong or inputs are invalid.
4

Termination condition

Specify when the Assistant’s job is complete.
Keep steps atomic, verifiable, and source-aware (RAG/IP Vault names). Add logging expectations and acceptance checks for robust operation.

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Advanced Considerations

When designing Assistants:
  • Name sources explicitly: Reference specific RAG or IP Vault documents by name
  • Include validation steps: Check inputs before processing
  • Define success criteria: What does “done correctly” look like?
  • Plan for edge cases: How should the Assistant handle unexpected inputs?
Start with simple Assistants and gradually add complexity as you understand the patterns that work well for your use cases.

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7 Error handling patterns for Assistants

Building robust Assistants requires thoughtful error handling and validation strategies. This ensures your Assistants can gracefully handle unexpected situations and provide useful feedback.

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Core Error Handling Patterns

Validate inputs

Check required fields and data types before processing. Ask targeted follow-ups when information is missing or unclear.

Constrain sources

Prefer specific RAG/IP Vault documents over free web searches. This ensures consistent, reliable information sources.

Plan-then-execute

Have the Assistant outline its plan before executing. This allows for validation and course correction early in the process.

Degrade gracefully

Return partial results plus a “next steps” list when complete execution isn’t possible. Never fail silently.

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Error Categories to Handle

Scenario: User provides incomplete, invalid, or ambiguous input.Response Strategy:
  • List specific fields that are missing
  • Provide examples of valid inputs
  • Ask targeted questions to gather needed information
  • Offer to restart from step 1 with clear inputs
Scenario: Referenced documents or data sources are not available.Response Strategy:
  • Identify which sources are missing
  • Suggest alternative sources if available
  • Ask user to provide or specify the correct sources
  • Explain what can and cannot be completed without the sources
Scenario: An intermediate step fails or produces unexpected results.Response Strategy:
  • Identify which step failed and why
  • Present what was successfully completed
  • Offer options to retry with different parameters
  • Suggest breaking the task into smaller steps
Scenario: User request is off-topic or outside the Assistant’s capabilities.Response Strategy:
  • Acknowledge the request
  • Explain the Assistant’s specific focus and capabilities
  • Redirect to the intended workflow
  • Suggest alternative Assistants or approaches if applicable

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Example Error Handling Implementation

Error Handling Protocol:

A- Invalid or Incomplete Input:
   - Identify missing required fields
   - Provide examples of valid input format
   - Ask: "Please provide [specific field] in [format]. Example: [example]"
   - Offer to restart from step 1

B- Source Not Available:
   - Report: "Cannot access [source name]"
   - Ask: "Please verify the document name or provide an alternative source"
   - List available alternatives if any exist

C- Processing Failure:
   - Report what was completed successfully
   - Explain where the failure occurred
   - Suggest: "We can try [alternative approach] or adjust [parameters]"

D- Off-Topic Request:
   - Acknowledge: "I understand you're asking about [topic]"
   - Clarify: "This Assistant focuses specifically on [scope]"
   - Redirect: "For [off-topic], please use [appropriate resource/Assistant]"
Well-designed error handling transforms frustrating failures into learning opportunities and improves the overall user experience.

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8 Advanced design with CRISPE

For more sophisticated and robust Assistants, explore the CRISPE methodology. This advanced template provides a structured approach to defining your Assistant’s capabilities, context, and desired outputs.

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Why CRISPE?

CRISPE is a structured methodology to define Capabilities, Role, Inputs, Steps, Policies, and Evaluation for robust, auditable Assistants. It ensures comprehensive Assistant design that covers all aspects of operation.

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The CRISPE Framework

1

Capabilities & constraints

What the Assistant can and cannot do. Define the boundaries of functionality clearly to set appropriate expectations.
2

Role & audience

Who it is and who it serves. Establish the persona and target user base for appropriate tone and depth.
3

Inputs & sources

Required fields and named RAG/IP Vault assets. Specify exactly what information the Assistant needs to operate effectively.
4

Steps & checkpoints

Atomic tasks with intermediate validations. Break down the workflow into verifiable stages with clear success criteria.
5

Policies & safety

Privacy, redaction, and compliance boundaries. Establish guardrails for data handling and output generation.
6

Evaluation & QA

Acceptance tests and quality thresholds. Define how to measure success and what constitutes acceptable output.

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CRISPE Template Structure

Assistant: [NAME]

CAPABILITIES:
- Can: [list specific capabilities]
- Cannot: [list explicit limitations]
- Requires: [dependencies and prerequisites]

ROLE:
- Identity: [who/what the Assistant is]
- Serves: [target audience]
- Purpose: [primary objective]

INPUTS:
- Required: [mandatory fields and formats]
- Optional: [nice-to-have inputs]
- Sources: [specific RAG/IP Vault documents by name]

STEPS:
1. [Step name]: [detailed action]
   - Checkpoint: [verification criteria]
2. [Step name]: [detailed action]
   - Checkpoint: [verification criteria]
[Continue for all steps]

POLICIES:
- Privacy: [data handling rules]
- Safety: [content boundaries]
- Compliance: [regulatory requirements]
- Errors: [handling strategies]

EVALUATION:
- Success criteria: [measurable outcomes]
- Quality metrics: [standards to meet]
- Acceptance tests: [validation steps]

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Benefits of CRISPE Design

Comprehensive

Covers all aspects of Assistant behavior and operation systematically.

Auditable

Creates clear documentation of what the Assistant should do and how.

Maintainable

Makes it easy to update and refine Assistant behavior over time.

Reliable

Reduces edge cases and unexpected behaviors through thorough design.
Learn more about building Assistants with CRISPE: Building Assistants with CRISPE
Start with the basic template and evolve to CRISPE as your Assistants become more complex or mission-critical.

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9 Iterate and validate with a tight loop

Effective use of Pria requires an iterative approach where you continuously refine your prompts and validate outputs using Agent Details and other feedback mechanisms.

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The Iteration Loop

1

Initial request

Start with a clear, specific prompt based on best practices.
2

Review output

Evaluate the response for accuracy, completeness, and alignment with your needs.
3

Check Agent Details

Examine which sources were used, which agents executed, and whether all steps succeeded.
4

Identify gaps

Determine what’s missing, incorrect, or could be improved.
5

Refine and retry

Adjust your prompt, add sources, or clarify requirements based on findings.
6

Repeat until satisfied

Continue the loop until outputs meet your acceptance criteria.

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Validation Request Template

"Run with sources A/B. In Agent Details, show: (1) retrieved passages,
(2) any inference steps, (3) unresolved items. If missing, request the exact inputs needed."

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What to Look For

  • Were the right documents consulted?
  • Are there missing sources that should be included?
  • Is the source information current and accurate?
  • Are all requested elements present?
  • Is the depth appropriate for your needs?
  • Are there gaps in coverage or reasoning?
  • Are facts verifiable and correctly cited?
  • Is there a clear distinction between retrieved facts and inferences?
  • Do numbers, dates, and specific details check out?
  • Does the tone match your requirements?
  • Is the structure logical and easy to follow?
  • Does it meet your stated success criteria?

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Refinement Strategies

When iteration reveals issues:

Add specificity

Make your requirements more precise and bounded.

Adjust sources

Add, remove, or replace reference documents.

Break down tasks

Split complex requests into smaller, sequential steps.

Clarify constraints

Make explicit what should and shouldn’t be included.
Treat outputs as drafts until Agent Details confirms the right sources were used and success criteria are met. This iterative validation ensures high-quality, reliable results.
Keep a log of what refinements worked well for different types of tasks. This builds your personal library of effective prompt patterns.

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10 Governance, privacy, and safety

Operating Pria responsibly requires attention to data governance, privacy protection, and safety considerations. These practices protect both you and your organization while ensuring compliant, ethical AI use.

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Core Governance Principles

Use IP Vault documents and RAG files instead of raw copy-paste or unvetted links. Structured sources provide:
  • Better traceability and audit trails
  • Controlled access and versioning
  • Cleaner, more reliable data
  • Easier compliance with data policies
Follow your organization’s privacy and safety policies:
  • Restrict sensitive content appropriately
  • Verify recipients for any exports
  • Use proper classification labels
  • Follow data retention policies
  • Respect geographic and regulatory boundaries
Maintain human review for outputs impacting:
  • Critical business decisions
  • Grades or evaluations
  • Compliance or legal matters
  • Policy creation or changes
  • Public communications
  • Financial transactions
AI assistance should augment, not replace, human judgment in high-stakes scenarios.
Be transparent about AI usage:
  • Disclose when content is AI-generated
  • Cite sources appropriately
  • Explain AI’s role in decision-making
  • Document processes for auditability

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Data Privacy Best Practices

1

Classify before sharing

Understand the sensitivity level of data before using it with Pria.
2

Use IP Vault for control

Store sensitive documents in IP Vault where access can be managed and tracked.
3

Minimize PII exposure

Redact or generalize personally identifiable information when possible.
4

Review before distribution

Check outputs for inadvertent disclosure of sensitive information.

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Safety Considerations

Safety encompasses both preventing harmful outputs and ensuring appropriate use of AI capabilities.
Content safety:
  • Review outputs for bias, fairness, and appropriateness
  • Ensure compliance with content policies
  • Validate factual claims, especially for sensitive topics
  • Consider potential misuse or misinterpretation
Operational safety:
  • Test Assistants thoroughly before production use
  • Implement fallbacks for critical workflows
  • Monitor for unexpected behaviors or errors
  • Have contingency plans for AI unavailability

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Compliance Framework

Different industries and regions have specific requirements:
  • Education: FERPA, COPPA, student privacy laws
  • Healthcare: HIPAA, patient confidentiality
  • Finance: SOX, PCI-DSS, financial regulations
  • Europe: GDPR and data protection rules
  • Government: FedRAMP, ITAR, specific agency requirements
For institutional commitments and protections, see your Praxis AI Data Processing Agreement (DPA) and internal governance policies.

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Ethical AI Use

Beyond compliance, consider ethical dimensions:
  • Fairness: Avoid perpetuating biases or discrimination
  • Accountability: Take responsibility for AI-assisted outputs
  • Transparency: Be clear about AI’s role and limitations
  • Beneficence: Use AI to create positive outcomes
  • Autonomy: Respect user agency and informed consent
When in doubt about governance, privacy, or safety, consult your organization’s AI governance team or compliance officer before proceeding.

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Putting it all together

Mastering Pria requires integrating all these practices into a cohesive workflow. Here’s how to combine them effectively:

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The Complete Workflow

1
Start a correctly named conversation
2
Set a clear perspective
3
Select precise files from IP Vault
4
State objective, constraints, and success criteria
5
Run
6
Inspect Agent Details
7
Refine inputs or steps
8
Repeat until acceptance tests pass
9
Templatize into an Assistant with CRISPE
10
Add fallback for edge cases

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Continuous Improvement

As you use Pria more:
  1. Build a prompt library: Save successful prompts and patterns
  2. Refine Assistants: Update based on real-world performance
  3. Document learnings: Note what works and what doesn’t
  4. Share knowledge: Help others learn from your experience
  5. Stay current: Follow Praxis AI updates and new capabilities

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Troubleshooting Common Issues

Generic outputs

Solution: Raise specificity (objective, structure, constraints) and narrow sources (IP Vault/RAG).

Incomplete results

Solution: Check Agent Details for missing or failing steps and adjust accordingly.

Wrong context

Solution: Verify you’re in the correct conversation and the right sources are referenced.

Inconsistent quality

Solution: Create an Assistant to standardize the workflow and ensure repeatability.
If results feel generic, raise specificity (objective, structure, constraints) and narrow sources (IP Vault/RAG). If results feel incomplete, check Agent Details for missing or failing steps and adjust accordingly.

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Success Indicators

You’re mastering Pria when:
  • First attempts consistently produce usable outputs
  • You can predict which sources and steps Pria will use
  • Assistants handle 80%+ of routine workflows
  • Agent Details shows successful execution with minimal inference
  • Iteration cycles are shorter and more targeted
  • Outputs require less manual editing
  • Colleagues ask you for tips and templates
Explore these resources to deepen your Praxis AI expertise:
  • Getting started: User Guide - Foundation for using Praxis AI
  • Building Assistants: Assistants Personalization - Advanced Assistant design with CRISPE
  • IP Vault: Learn how to effectively scrape and manage website content
  • Prompt Engineering: Master the art of crafting effective prompts
  • Agent System: Understand how Pria’s agent architecture works
Bookmark this guide and refer back to it regularly as you develop your Praxis AI skills. Mastery comes through consistent application of these practices.