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Intent Weighting

Table Of Contents

Intent Weighting is an advanced feature planned for AgenticAPI v0.4.0, designed to optimize action selection for AI agents by providing metadata that quantifies the cost, priority, and risk of each action. Using OpenAPI extensions like x-intent-weighting, AgenticAPI will enable agents to make informed decisions when choosing among multiple actions (e.g., SUMMARIZE vs. TRANSLATE), balancing factors such as computational cost, urgency, or potential impact. This document explains the concept of intent weighting and provides an example of its planned implementation.

How Intent Weighting Works #

Intent Weighting attaches metadata to action verbs, describing their operational characteristics. This metadata helps agents evaluate trade-offs and select the most appropriate action based on context, constraints, or optimization goals. Key weighting factors include:

  • Priority: Indicates urgency (e.g., high, medium, low).
  • Cost Estimate: Quantifies resource usage, such as computational cost or API fees (e.g., in USD).
  • Risk Profile: Assesses potential errors or side effects (e.g., low, high).
  • Execution Time: Estimates processing duration (e.g., in seconds).

The x-intent-weighting OpenAPI extension will embed these factors in endpoint definitions, allowing agents to query and compare actions dynamically.

Example: OpenAPI with Intent Weighting #

The following OpenAPI snippet demonstrates how x-intent-weighting will be applied to the SUMMARIZE and TRANSLATE verbs, enabling agents to choose based on cost and risk.

YAML
paths:
  /document:
    summarize:
      x-action: summarize
      x-category: compute
      x-intent-weighting:
        priority: high
        cost_estimate: 0.01  # USD per request
        risk_profile: low
        execution_time: 2.0  # seconds
      summary: Summarize a document
      operationId: summarizeDocument
      requestBody:
        required: true
        content:
          application/json:
            schema:
              type: object
              properties:
                document_id:
                  type: string
                format:
                  type: string
                  enum: [text, bullets]
                max_words:
                  type: integer
                style:
                  type: string
                  enum: [neutral, formal, casual]
      responses:
        '200':
          description: Successful response
          content:
            application/json:
              schema:
                type: object
                properties:
                  summary:
                    type: string
                  title:
                    type: string
  /translate:
    translate:
      x-action: translate
      x-category: compute
      x-intent-weighting:
        priority: medium
        cost_estimate: 0.05  # USD per request
        risk_profile: medium
        execution_time: 5.0  # seconds
      summary: Translate a document
      operationId: translateDocument
      requestBody:
        required: true
        content:
          application/json:
            schema:
              type: object
              properties:
                document_id:
                  type: string
                target_language:
                  type: string
      responses:
        '200':
          description: Successful response
          content:
            application/json:
              schema:
                type: object
                properties:
                  translated_text:
                    type: string
  • x-intent-weighting:
    • SUMMARIZE: High priority, low cost ($0.01), low risk, fast (2 seconds).
    • TRANSLATE: Medium priority, higher cost ($0.05), medium risk, slower (5 seconds).
  • Agent Decision: An agent needing a quick, low-cost action might choose SUMMARIZE, while one requiring translation accepts higher cost and risk.

Example Agent Logic (Python):

Python
import httpx
import json

def select_action(actions):
    # Simulate agent choosing based on intent weighting
    best_action = None
    best_score = float('inf')  # Minimize cost and time
    for action in actions:
        weighting = action.get('x-intent-weighting', {})
        score = weighting.get('cost_estimate', 0) + weighting.get('execution_time', 0)
        if score < best_score:
            best_score = score
            best_action = action
    return best_action

# Fetch OpenAPI schema (planned DISCOVER /actions)
with httpx.Client() as client:
    response = client.get("http://localhost:8000/openapi.json")
    openapi = response.json()

# Extract actions (simulated for v0.4.0)
actions = [
    openapi["paths"]["/document"]["summarize"],
    openapi["paths"]["/translate"]["translate"]
]

# Select optimal action
chosen_action = select_action(actions)
print(f"Chosen action: {chosen_action['x-action']}")

Output:

Plaintext
Chosen action: summarize

This agent selects SUMMARIZE due to its lower cost and execution time, demonstrating intent weighting in action.

Benefits #

  • Optimized Decisions: Agents choose actions based on cost, risk, or priority.
  • Dynamic Adaptation: Weighting supports context-aware action selection.
  • Transparency: Metadata clarifies operational impacts for developers and agents.

Best Practices #

  • Define Clear Metrics: Ensure cost_estimate and execution_time are accurate.
  • Balance Factors: Adjust priority and risk_profile to reflect use case needs.
  • Document Weighting: Include x-intent-weighting in all action endpoints.
  • Plan for v0.4.0: Prepare agents to parse weighting metadata when available.

Next Steps #

  • Learn about Test Mode for action simulation.
  • Explore Chaining for workflow orchestration.
  • Try Implementing Custom Verbs with planned weighting.
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Updated on May 29, 2025