Intelligence Brief API — Multi-Source Narrative Analysis

The Intelligence Brief API aggregates signals from up to six platforms — X, Reddit, YouTube, News, Web, and Financial — and produces a forensic narrative analysis covering authenticity scoring, emotion profiling, primary narratives, adversary tracking, and financial market correlations. Each run costs 2 credits and requires a signed-in account.

Intelligence Brief is in beta. The response schema is versioned (currently v2.4) and may gain new optional fields in future releases. All new fields are additive; existing fields will not be removed or renamed without a major version bump.

POST /api/intelligence/analyze

Generate a new Intelligence Brief for one or more search terms across selected platforms.

POST https://www.rhetoricaudit.com/api/intelligence/analyze
Content-Type: application/json

Authentication

This endpoint requires a signed-in Rhetoric Audit account. Authentication is resolved from your session cookie (web dashboard) or Supabase session token. Anonymous requests receive a 401 response.

Rate limits

In addition to the credit cost, per-user rate limits apply:

Window	Limit
Per hour	5 requests
Per day	50 requests

Request

string[]

required

One or more search terms to analyze. The engine fetches cross-platform signals matching these terms. Minimum 1 term, maximum 10 terms. Each term must be a non-empty string.

string[]

required

The platforms to pull signals from. Must contain at least one value. Accepted values (lowercase): x, reddit, youtube, news, web, financial.

number

required

Maximum number of signals to collect across all sources. Must be an integer between 10 and 200.

Response

boolean

true when the brief was successfully generated and persisted.

object

The full Intelligence Brief result. See the brief fields section below.

object

Credit consumption details for this request.

Show credits fields

number

Credits consumed by this request (always 2).

number

Your credit balance after this request.

string

USD cost as a fixed-decimal string, e.g. "0.60".

object

Timing breakdown for the request.

Show performance fields

number

Time spent fetching signals from external sources.

number

Time spent in LLM analysis.

number

Total request duration.

string

The LLM model that produced the analysis, e.g. "openai/gpt-4o-mini".

string[]

Optional array of non-fatal warnings, such as partial source failures or mock data usage. Omitted when there are no warnings.

object

Diagnostic information about which sources succeeded or failed.

Show data_quality fields

boolean

true if one or more sources failed to return data.

string[]

Source IDs that returned data successfully.

string[]

Source IDs that failed or timed out.

boolean

true if mock data was substituted (only possible in non-production environments).

Brief fields

The brief object contains the full IntelligenceBriefResult. All fields marked optional are additive and may be absent in results from earlier schema versions.

string

UUID of the saved brief record in the database.

string

ISO 8601 timestamp when the brief was saved.

string

A prose summary of the key findings across all signals and narratives.

number

Overall authenticity of the signal set, 0–100. Lower scores indicate higher likelihood of coordinated or inauthentic activity.

string

Evidence-based explanation of the authenticity_score. Present in schema v2.1+.

object

Aggregate emotional signal across all analyzed content.

Show emotion_profile fields

number

0–100

number

0–100

number

0–100

number

0–100

number

0–100

number

0–100

array

Array of dominant narratives detected across platforms.

Show primary_narratives item fields

string

Short title for the narrative.

string

Prose description of the narrative’s content and framing.

number

Percentage of signals carrying this narrative, 0–100.

string[]

Platforms where this narrative appears.

string

One of "rising", "stable", or "declining".

string

Optional. How quickly the narrative spread, e.g. "Rapid (jumped from X to News in <24h)".

string

Optional. "low", "medium", or "high".

string

Optional. "Yes" or "No" — whether the narrative is confined to a single ideological cluster.

array

High-signal accounts or sources the LLM identified as authoritative on the topic.

Show expert_shortlist item fields

string

Account handle or source name.

string

Platform identifier: x, reddit, youtube, news, or web.

string

Description of why this source is considered expert.

number

Number of signals attributed to this source in the dataset.

number

Source verification confidence, 0–100.

object

Structured risk evaluation of the narrative landscape.

Show risk_assessment fields

string

One of "low", "medium", "high", or "critical".

string[]

Array of specific risk factors identified.

string[]

Recommended actions to counter the identified risks.

number

Confidence in the risk assessment, 0–100.

string

Optional. Predicted longevity, e.g. "Short-term (72h)" or "Permanent".

string

Optional. Likelihood of recurrence.

string

Optional. Whether this narrative pattern has appeared before.

object

Breakdown of how many signals were analyzed per platform.

Show signal_stats fields

number

Total signal count.

number

Signal count from X (optional).

number

Signal count from Reddit (optional).

number

Signal count from YouTube (optional).

number

Signal count from News sources (optional).

number

Signal count from Web sources (optional).

number

Signal count from Financial sources (optional).

array

Optional (v2.2+). Accounts identified as primary drivers of adversarial narratives.

Show narrative_adversaries item fields

string

Account handle.

string

Lowercase platform identifier.

string

Tactics employed, e.g. "Temporal clustering, Copy-paste repetition, Emotional baiting".

string

Description of the impact, e.g. "Primary driver of Fear spike".

number

Authenticity score 0–100. Lower values indicate more coordinated or inauthentic behavior.

object

Optional (v2.2+). Coordination evidence and technical indicators.

Show audit_trail fields

string

Summary of coordination evidence observed.

string

One of "low", "medium", or "high".

string

Observed technical signals such as timestamp clustering, handle patterns, or phrase echoes.

array

Optional (v2.3+). Records where social signals preceded institutional signals.

Show time_delta_flags item fields

ISO 8601 timestamp of the social signal.

string

ISO 8601 timestamp of the corresponding institutional signal.

number

Time difference in minutes. Negative values mean social led institutional.

string

One of "LEADING_NARRATIVE_ATTACK", "TRAILING", or "SYNCHRONOUS".

string

Optional excerpt from the leading signal.

object

Optional (v2.3+). Dissonance gauge comparing social vs. institutional sentiment.

Show visual_blueprint fields

string

Always "dissonance_gauge".

Aggregated social sentiment score, 0–100.

number

Aggregated institutional sentiment score, 0–100.

string

The topic being measured.

string

Prose interpretation of the dissonance gap.

array

Optional (v2.4+). Tickers and market theses the LLM infers from narrative signals.

Show financial_correlations item fields

string

Exchange ticker symbol, e.g. "TCS.NS". Empty string for non-listed entities.

string

Human-readable company name.

string

Optional SEC/EDGAR/exchange filing ID if cited.

string

One of "positive", "negative", or "neutral".

string

One of "high", "medium", or "low".

string

One-sentence explanation of how the narrative connects to a market outcome.

number

Optional. How many hours ahead of market open or next earnings the signal precedes.

Code example

curl -X POST https://www.rhetoricaudit.com/api/intelligence/analyze \
  -H "Content-Type: application/json" \
  -H "Cookie: <your-session-cookie>" \
  -d '{
    "search_terms": ["semiconductor tariffs", "chip shortage"],
    "sources": ["x", "reddit", "news", "financial"],
    "max_items": 100
  }'

const response = await fetch(
  'https://www.rhetoricaudit.com/api/intelligence/analyze',
  {
    method: 'POST',
    credentials: 'include', // sends session cookie
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify({
      search_terms: ['semiconductor tariffs', 'chip shortage'],
      sources: ['x', 'reddit', 'news', 'financial'],
      max_items: 100,
    }),
  }
);

const data = await response.json();
console.log(data.brief.authenticity_score);
console.log(data.brief.risk_assessment.overall_risk_level);
console.log(data.credits.remaining);

Error responses

Status	When it occurs
`400`	Invalid request body (Zod validation failure) or insufficient signals found (fewer than 5 real signals returned by sources)
`401`	User is not authenticated
`402`	Insufficient credits — body includes `required` and `available` fields
`429`	Rate limit exceeded — response includes `retry_after_seconds` and a `Retry-After` header
`500`	Server error, LLM processing failure, or database save failure

GET /api/intelligence/briefs

Retrieve a paginated list of your historical Intelligence Briefs.

GET https://www.rhetoricaudit.com/api/intelligence/briefs

Authentication

Requires a signed-in session. Returns 401 for unauthenticated requests.

Query parameters

number

default:"20"

Number of briefs to return per page. Maximum 100.

number

default:"0"

Zero-based offset for pagination.

string

default:"date"

Sort field. Accepted values: date, signal_count.

string

default:"desc"

Sort direction. Accepted values: asc, desc.

string

default:"all"

Time window filter. Accepted values: all, week (last 7 days), month (last 30 days).

Response

array

Array of brief records. Each item has the same shape as the brief field returned by POST /api/intelligence/analyze, plus id and created_at.

number

Total number of briefs matching the query (before pagination). Use this with limit and offset to implement page controls.

Example

curl "https://www.rhetoricaudit.com/api/intelligence/briefs?limit=10&sort=date&order=desc&filter=week" \
  -H "Cookie: <your-session-cookie>"

{
  "briefs": [
    {
      "id": "d4e5f6a7-...",
      "created_at": "2026-05-09T10:23:00.000Z",
      "search_terms": ["semiconductor tariffs"],
      "sources_used": ["x", "reddit", "news", "financial"],
      "signal_count": 87,
      "executive_summary": "...",
      "authenticity_score": 64,
      "risk_assessment": { "overall_risk_level": "high", ... }
    }
  ],
  "total": 3
}

Overview

Endpoints

Intelligence Brief API — Multi-Source Narrative Analysis

POST /api/intelligence/analyze

Authentication

Rate limits

Request

Response

Brief fields

Code example

Error responses

GET /api/intelligence/briefs

Authentication

Query parameters

Response

Example

​POST /api/intelligence/analyze

​Authentication

​Rate limits

​Request

​Response

​Brief fields

​Code example

​Error responses

​GET /api/intelligence/briefs

​Authentication

​Query parameters

​Response

​Example

POST /api/intelligence/analyze

Authentication

Rate limits

Request

Response

Brief fields

Code example

Error responses

GET /api/intelligence/briefs

Authentication

Query parameters

Response

Example