Overview
TheGenerateArgumentBlueprintOutput schema defines the complete output from the generateArgumentBlueprint flow. It contains the argument blueprint, analysis, social pulse, and detected fallacies.
This is the primary data structure used throughout Argument Cartographer.
Schema Definition
src/ai/flows/generate-argument-blueprint.ts:77
Fields
Core Analysis
A structured JSON blueprint of the arguments.Array of argument nodes forming a tree structure. See Argument Node Schema.
A concise, neutral summary of the overall state of the debate.Typically 2-4 paragraphs providing an objective overview.
AI-driven meta-analysis providing novel insights, identifying emerging themes, logical gaps, or the overall state of the debate.Deeper analysis than summary, includes:
- Emerging themes and patterns
- Logical gaps in arguments
- Quality of evidence on both sides
- State of the debate overall
Quality Metrics
A score from 1-10 rating the overall quality, diversity, and reliability of the sources found.Factors considered:
- Source diversity (number of unique outlets)
- Source reputation (trusted vs unknown)
- Evidence quality (primary vs secondary sources)
- Balanced coverage (both sides represented)
Additional Insights
A candid, slightly cynical, “no-BS” summary of the situation, written in simple, conversational language.Example: “Look, both sides have points, but most of the debate is just people yelling past each other. The real issue is [X], but nobody wants to talk about that.”
A list of 3-5 key takeaways or summary points.Bullet-point style insights that capture the essence of the debate.
Social Context
A summary of the public sentiment and key discussion points on the topic from social media platform X (Twitter).Generated from analyzing recent tweets, written in a “Grok-style” conversational tone.
An array of relevant tweets from X/Twitter (up to 5 tweets).Sorted by engagement (like count). Each tweet includes:
id: Tweet IDtext: Full tweet textauthor: Author details (name, username, profile image)created_at: Timestamppublic_metrics: Engagement metrics (likes, retweets, replies, impressions)
Fallacy Detection
An array of logical fallacies detected in the source material.Optional field. See Fallacy Detection Schema for structure.
Example Output
Usage
This output is used throughout the application:- Visualization: Blueprint rendered in various graph layouts
- Analysis Display: Summary and analysis shown to users
- Quality Indicator: Credibility score displayed
- Social Context: Social pulse and tweets provide public sentiment
- Fallacy Highlighting: Detected fallacies marked in UI
- Chat Context: Full output passed to Ask More flow
Validation
The schema enforces:blueprintmust be a non-empty arraycredibilityScoremust be between 1 and 10keyPointsshould contain 3-5 items (recommended)tweetslimited to 5 items in practice- All required fields must be present
Post-Processing
The flow applies these transformations:- Credibility Score: Converts decimal (0.9) to 1-10 scale (9) if needed
- Source URLs: Replaces “null” strings with placeholder URLs
- Parent IDs: Converts “null” strings to actual
null - Tweet Sorting: Sorts by like count before limiting to 5
Related
- Argument Node Schema
- Fallacy Detection Schema
- Generate Blueprint Flow
- Ask More Flow - uses this output as context
