> ## Documentation Index
> Fetch the complete documentation index at: https://docs.medstrato.com/llms.txt
> Use this file to discover all available pages before exploring further.

# List Signals

> Retrieve regulatory and industry signals with AI-powered analysis.

## Query Parameters

<ParamField query="page" type="integer" default="1">
  Page number
</ParamField>

<ParamField query="per_page" type="integer" default="20">
  Results per page (max 100)
</ParamField>

<ParamField query="source" type="string">
  Filter by source. Options: `fda`, `ema`, `nmpa`, `pmda`, `tga`, `health_canada`, `mhra`, `industry`
</ParamField>

<ParamField query="impact" type="string">
  Filter by impact level. Options: `critical`, `high`, `medium`, `low`
</ParamField>

<ParamField query="sentiment" type="string">
  Filter by sentiment. Options: `positive`, `neutral`, `negative`
</ParamField>

<ParamField query="product_id" type="string">
  Filter signals relevant to a specific product
</ParamField>

<ParamField query="is_bookmarked" type="boolean">
  Filter bookmarked signals only
</ParamField>

<ParamField query="is_read" type="boolean">
  Filter by read/unread status
</ParamField>

<ParamField query="search" type="string">
  Full-text search in title and content
</ParamField>

<ParamField query="published_after" type="string">
  Filter signals published after this date (ISO 8601)
</ParamField>

## Response

<ResponseField name="data" type="array">
  <Expandable title="Signal object">
    <ResponseField name="id" type="string">
      Unique identifier
    </ResponseField>

    <ResponseField name="title" type="string">
      Signal title
    </ResponseField>

    <ResponseField name="url" type="string">
      Source URL
    </ResponseField>

    <ResponseField name="source" type="object">
      Source details (name, country, region)
    </ResponseField>

    <ResponseField name="content" type="string">
      Full content text
    </ResponseField>

    <ResponseField name="ai_summary" type="string">
      AI-generated summary
    </ResponseField>

    <ResponseField name="impact" type="object">
      <Expandable title="Impact assessment">
        <ResponseField name="level" type="string">
          Impact level (critical, high, medium, low)
        </ResponseField>

        <ResponseField name="score" type="number">
          Impact score (0-100)
        </ResponseField>

        <ResponseField name="categories" type="array">
          Affected categories
        </ResponseField>
      </Expandable>
    </ResponseField>

    <ResponseField name="sentiment" type="string">
      Sentiment (positive, neutral, negative)
    </ResponseField>

    <ResponseField name="product_relevance" type="array">
      Relevant products with relevance type
    </ResponseField>

    <ResponseField name="is_read" type="boolean">
      Read status
    </ResponseField>

    <ResponseField name="is_bookmarked" type="boolean">
      Bookmark status
    </ResponseField>

    <ResponseField name="published_at" type="string">
      Publication timestamp
    </ResponseField>

    <ResponseField name="fetched_at" type="string">
      Fetch timestamp
    </ResponseField>
  </Expandable>
</ResponseField>

<RequestExample>
  ```bash cURL theme={null}
  curl -X GET "https://api.medstrato.com/v1/signals?source=fda&impact=high&per_page=10" \
    -H "Authorization: Bearer sk_live_your_api_key"
  ```

  ```javascript Node.js theme={null}
  const signals = await medstrato.signals.list({
    source: 'fda',
    impact: 'high',
    per_page: 10
  });
  ```

  ```python Python theme={null}
  signals = medstrato.signals.list(
      source='fda',
      impact='high',
      per_page=10
  )
  ```
</RequestExample>

<ResponseExample>
  ```json Response theme={null}
  {
    "data": [
      {
        "id": "sig_abc123",
        "title": "FDA Issues Updated Guidance on AI/ML-Based Medical Devices",
        "url": "https://www.fda.gov/medical-devices/...",
        "source": {
          "name": "FDA",
          "country": "US",
          "region": "North America"
        },
        "ai_summary": "The FDA has released updated guidance clarifying the regulatory pathway for AI/ML-based medical devices, emphasizing the importance of continuous learning algorithms and predetermined change control plans.",
        "impact": {
          "level": "high",
          "score": 85,
          "categories": ["regulatory", "ai_ml", "software"]
        },
        "sentiment": "neutral",
        "product_relevance": [
          {
            "product_id": "prod_xyz789",
            "product_name": "CardioAI Diagnostic System",
            "relevance_type": "direct",
            "relevance_score": 0.92
          }
        ],
        "is_read": false,
        "is_bookmarked": false,
        "published_at": "2024-01-18T16:00:00Z",
        "fetched_at": "2024-01-18T18:30:00Z"
      }
    ],
    "meta": {
      "page": 1,
      "per_page": 10,
      "total": 23,
      "unread_count": 8
    }
  }
  ```
</ResponseExample>