On Activation

1. Read brand/positioning.md, brand/competitors.md, and brand/landscape.md if present. Use them to sharpen queries and exclusions. All optional - works at zero brand context.
2. Confirm Exa auth: Exa MCP connected, or EXA_API_KEY set (mktg doctor --json --fields integrations). If neither, stop and surface: get a key at https://dashboard.exa.ai/api-keys then export EXA_API_KEY=....
3. Prefer MCP tools when present; otherwise use the cURL examples below.
4. After discovery, chain firecrawl or exa-contents only when a known URL needs deeper extraction.

Exa Search

Requires API key: Get one at https://dashboard.exa.ai/api-keys

Header: x-api-key: $EXA_API_KEY

Use POST https://api.exa.ai/search for semantic web retrieval, ranked results, and optional result-level extraction in one raw HTTP call. Start with type: "auto" for general retrieval. Add contents only when the caller needs page text, highlights, summaries, freshness-controlled crawling, subpages, or extracted links.

Quick Start (cURL)

Basic search

curl -sS -X POST "https://api.exa.ai/search" \
  -H "Content-Type: application/json" \
  -H "x-api-key: $EXA_API_KEY" \
  -d '{
    "query": "latest developments in LLMs",
    "type": "auto",
    "numResults": 10
  }'

Search with highlights

curl -sS -X POST "https://api.exa.ai/search" \
  -H "Content-Type: application/json" \
  -H "x-api-key: $EXA_API_KEY" \
  -d '{
    "query": "latest developments in LLMs",
    "type": "auto",
    "numResults": 5,
    "contents": {
      "highlights": true
    }
  }'

With filters and freshness

curl -sS -X POST "https://api.exa.ai/search" \
  -H "Content-Type: application/json" \
  -H "x-api-key: $EXA_API_KEY" \
  -d '{
    "query": "AI regulation policy updates",
    "type": "auto",
    "category": "news",
    "numResults": 10,
    "includeDomains": ["reuters.com", "bbc.com"],
    "startPublishedDate": "2025-01-01",
    "contents": {
      "text": {
        "maxCharacters": 2000
      },
      "maxAgeHours": 24,
      "livecrawlTimeout": 12000
    }
  }'

Deep search

curl -sS -X POST "https://api.exa.ai/search" \
  -H "Content-Type: application/json" \
  -H "x-api-key: $EXA_API_KEY" \
  -d '{
    "query": "map the major technical and commercial tradeoffs in sodium-ion batteries for grid storage",
    "type": "deep",
    "numResults": 8
  }'

Endpoint

POST https://api.exa.ai/search

Authentication: x-api-key: <API_KEY> header. Exa also accepts Authorization: Bearer <API_KEY>, but prefer x-api-key in cURL examples for consistency.

Use this endpoint when the agent needs search results. If the agent already has URLs and only needs extraction, use POST /contents instead.

Parameters

Core request parameters

Parameter	Type	Required	Default	Description
query	string	Yes	-	Natural-language search query. Long, semantically rich descriptions work well.
type	string	No	auto	Search method: auto, fast, instant, deep-lite, deep, or deep-reasoning.
numResults	integer	No	10	Number of results to return. Use small values for agent loops; maximum is 100.
category	string	No	-	Specialized result type: company, people, research paper, news, personal site, or financial report.
includeDomains	string[]	No	-	Only return results from these domains, paths, or wildcard patterns. Max 1200.
excludeDomains	string[]	No	-	Exclude these domains, paths, or wildcard patterns. Max 1200.
startPublishedDate	string	No	-	ISO 8601 lower bound for result publication date.
endPublishedDate	string	No	-	ISO 8601 upper bound for result publication date.
userLocation	string	No	-	Two-letter ISO country code such as US or GB.
moderation	boolean	No	false	Filter unsafe content from results.
additionalQueries	string[]	No	-	Extra query variants for deep-search variants. Use alongside the main query.
systemPrompt	string	No	-	Instructions for synthesized output and deep-search planning, such as source preferences.
outputSchema	object	No	-	JSON Schema controlling output.content. Adds synthesized output and grounding.
stream	boolean	No	false	If true, returns SSE instead of a single JSON response.
compliance	string	No	-	Enterprise-only compliance mode, such as hipaa, when enabled for the account.

Content parameters nested under contents

On /search, text, highlights, and summary must be nested under contents.

Parameter	Type	Required	Default	Description
contents.text	boolean or object	No	-	Return full page text as markdown. Object form supports maxCharacters, includeHtmlTags, verbosity, includeSections, and excludeSections.
contents.highlights	boolean or object	No	-	Return query-relevant excerpts. Prefer true for agent workflows unless a fixed character budget is required.
contents.summary	boolean or object	No	-	Return per-result LLM summaries. Use sparingly because each result adds synthesis work.
contents.maxAgeHours	integer	No	-	Freshness control. 0 always live crawls; -1 uses cache only; omit for default cache-first behavior with crawl fallback.
contents.livecrawlTimeout	integer	No	10000	Timeout for live crawling in milliseconds. Use 10000 to 15000 for most freshness-sensitive calls.
contents.subpages	integer	No	0	Number of linked subpages to crawl per result.
contents.subpageTarget	string or string[]	No	-	Terms used to prioritize which subpages matter, such as ["api", "pricing"].
contents.extras.links	integer	No	0	Number of links to extract from each result page.
contents.extras.imageLinks	integer	No	0	Number of image URLs to extract from each result page.

Text object options

Parameter	Type	Default	Description
maxCharacters	integer	-	Character limit for returned text. Use this instead of tokensNum.
includeHtmlTags	boolean	false	Preserve HTML tags in output.
verbosity	string	compact	compact, standard, or full. Pair fresh section-aware extraction with contents.maxAgeHours: 0.
includeSections	string[]	-	Only include selected sections: header, navigation, banner, body, sidebar, footer, metadata.
excludeSections	string[]	-	Exclude selected sections from the same section list.

Highlights object options

Prefer contents.highlights: true for the highest-quality default. Only use object form when the agent needs a custom focus or budget.

Parameter	Type	Default	Description
query	string	-	Custom query guiding which excerpts are returned.
maxCharacters	integer	-	Cap highlight characters per URL. Omit unless the caller has a strict budget.

Summary object options

Parameter	Type	Default	Description
query	string	-	Custom query for the summary.
schema	object	-	JSON Schema for structured per-result summaries.

Search Types

Search type controls the retrieval and synthesis mode. Pick the mode for the workflow, not just the output format. outputSchema can be used with any search type; use deeper modes when the search process itself needs more planning, synthesis, or reasoning.

Type	Best for	Tradeoff
auto	General default search and most new integrations	Balances speed and quality without requiring the caller to tune retrieval strategy.
fast	Low-latency agent loops and product paths	Faster than auto; use when responsiveness matters more than maximum reasoning depth.
instant	Real-time UI, chat, voice, and autocomplete-style paths	Lowest latency path; use for quick retrieval rather than deep synthesis.
deep-lite	Lightweight research or synthesis	Adds more planning and synthesis than auto while staying lighter than full deep.
deep	Multi-step research, comparisons, and synthesis-heavy retrieval	Higher latency; better when the query needs exploration across several sources.
deep-reasoning	Hard research tasks with high ambiguity or complex tradeoffs	Highest latency and reasoning depth.

Use auto unless latency or reasoning depth is the primary constraint. Use fast or instant for time-sensitive calls. Use deep, deep-lite, or deep-reasoning when the query needs multi-step source discovery, comparison, or synthesis.

Mode-only examples

{
  "query": "recent product launches from major AI chip companies",
  "type": "fast",
  "numResults": 5
}

{
  "query": "compare competing explanations for the recent rise in grid-scale battery deployments",
  "type": "deep",
  "numResults": 8
}

Structured Output

Use systemPrompt for behavior and outputSchema for shape.

curl -sS -X POST "https://api.exa.ai/search" \
  -H "Content-Type: application/json" \
  -H "x-api-key: $EXA_API_KEY" \
  -d '{
    "query": "compare the latest frontier AI model releases",
    "type": "deep",
    "systemPrompt": "Prefer official sources and avoid duplicate results.",
    "outputSchema": {
      "type": "object",
      "properties": {
        "models": {
          "type": "array",
          "items": {
            "type": "object",
            "properties": {
              "name": { "type": "string" },
              "notable_claims": {
                "type": "array",
                "items": { "type": "string" }
              }
            },
            "required": ["name", "notable_claims"]
          }
        }
      },
      "required": ["models"]
    },
    "contents": {
      "highlights": true
    }
  }'

Keep schemas compact and bounded. Do not add citation fields to the schema; grounding is returned separately in output.grounding.

Streaming

Streaming applies to synthesized output, so include outputSchema along with -N, Accept: text/event-stream, and stream: true. Without outputSchema, the endpoint returns the normal JSON search response even when stream is true.

curl -sS -N -X POST "https://api.exa.ai/search" \
  -H "Content-Type: application/json" \
  -H "Accept: text/event-stream" \
  -H "x-api-key: $EXA_API_KEY" \
  -d '{
    "query": "recent grid-scale battery deployments",
    "type": "deep",
    "stream": true,
    "outputSchema": {
      "type": "object",
      "properties": {
        "summary": { "type": "string" }
      },
      "required": ["summary"]
    },
    "contents": {
      "highlights": true
    }
  }'

Treat streaming as SSE rather than JSON. Each data: frame contains an OpenAI-compatible chat completion chunk; read partial text from choices[0].delta.content and handle completion or error frames defensively.

Response Fields

Field	Type	Description
requestId	string	Unique request identifier.
results	array	Ranked result objects.
results[].title	string	Page title.
results[].url	string	Page URL.
results[].publishedDate	string or null	Estimated publication date when available.
results[].author	string or null	Author when available.
results[].text	string	Returned when contents.text is requested.
results[].highlights	string[]	Returned when contents.highlights is requested.
results[].highlightScores	number[]	Similarity scores for highlights.
results[].summary	string	Returned when contents.summary is requested.
results[].subpages	array	Nested result objects from subpage crawling.
results[].extras.links	string[]	Extracted links when requested.
output.content	string or object	Synthesized output when outputSchema is provided.
output.grounding	array	Citations and confidence labels for synthesized fields.
costDollars.total	number	Total request cost when returned.
searchTime	number	Search latency when returned.

Anti-Patterns

• Keep text, highlights, and summary inside contents on /search.
• Do not send top-level text, highlights, or summary; that shape belongs to /contents.
• Do not send tokensNum; use contents.text.maxCharacters to cap extracted text.
• Do not use useAutoprompt, numSentences, or highlightsPerUrl in new requests.
• Prefer contents.maxAgeHours over older livecrawl examples.
• Use documented categories only: company, people, research paper, news, personal site, and financial report.
• Avoid invalid category/filter combinations. company and people do not support startPublishedDate or endPublishedDate. company supports excludeDomains; people does not, and people only accepts LinkedIn domains in includeDomains.
• Pick one of contents.highlights, contents.text, or contents.summary by default. Stack modes only when the caller truly needs multiple views of each page.
• Expect SSE only when stream: true is paired with outputSchema; otherwise /search returns its normal JSON response.

Attribution

Ported from exa-labs/agent-skills - adapted for mktg's drop-in contract on 2026-07-18.

Upstream commit: 390ffee2d7e1d0dce2ed8efe4994c2b3c1c0173b

Drift detection: if the upstream skill changes, re-run mktg-steal https://github.com/exa-labs/agent-skills to evaluate the diff.