Agentic Search

Let Cybernaut-1 plan multi-angle retrieval, probe the index, and return a deep ranked result set.

POST/search/v2/search

Related NOSIBLE resources

research & data

Inspect the Search data dictionary or read NOSIBLE research for implementation context and methods.

Authorizations

apiKey

Api-Keystringrequiredheader

Your NOSIBLE API key.

Example: nos_sk_...

Body

application/json

promptstringbody

The research question for the agent to investigate. Defaults to a general AI-startup news prompt; when supplied, use at least 25 characters and include the decision, universe, or time window you care about.

Example: Which semiconductor companies are increasing AI infrastructure investment, and what evidence supports the change?

agentstringbody

Agent profile. cybernaut-1 is the current production agent.

Example: cybernaut-1

How to use this endpoint

guidance

Use Agentic Search when the question is broad, multi-angle, or hard to express as one query. The agent generates and evaluates a search strategy, then returns the final evidence set in the standard Search envelope. Prompts must be at least 25 characters and should state the decision or research question you need answered.

Response body

application/json

These are the fields you can build against. Nested names use dot notation; optional sections are called out in their descriptions.

messagestring

Human-readable summary of the work performed, including how many indexed records were evaluated and how long retrieval took.

Example: Evaluated 1,204,332 out of 15,311,040 records in 0.184 seconds.

queryobject

The effective query after defaults, filters, and search controls have been applied. Persist this object with results when you need reproducibility.

Example: { "question": "What is driving AI chip demand?", "algorithm": "hybrid-3", "n_results": 10 }

query.questionstring

Question used for retrieval.

Example: What is driving AI chip demand?

query.algorithmstring

Scoring algorithm actually used.

Example: hybrid-3

query.n_resultsinteger

Effective result cap.

Example: 10

query.n_probesinteger

Effective shard/collection probe count.

Example: 30

query.n_contextifyinteger

Effective context budget per result.

Example: 256

responseobject[]

Ranked result documents. Results are ordered by the selected algorithm's relevance score.

Example: [{ ... }]

response[].url_hashstring

Stable internal document hash. Use it as an opaque identifier; do not construct URLs from it.

Example: a1b2c3d4...

response[].urlstring

Canonical URL of the matching document.

Example: https://www.reuters.com/technology/...

response[].netlocstring

Source host extracted from the canonical URL.

Example: reuters.com

response[].publisheddate-time | null

Indexed publication timestamp when the source provided one.

Example: 2026-07-20T12:00:00Z

response[].visiteddate-time | null

Timestamp at which NOSIBLE fetched the document.

Example: 2026-07-20T12:04:11Z

response[].languagestring

Indexed document language classification.

Example: en-en

response[].authorstring | null

Author metadata when available.

Example: Jane Doe

response[].titlestring

Document title as indexed by NOSIBLE.

Example: Chipmakers increase AI infrastructure investment

response[].descriptionstring

Indexed page description or metadata summary when available.

Example: A review of data-center investment trends.

response[].best_chunkstring

Highest-scoring context window for this result.

Example: Demand for accelerated computing...

response[].contentstring

Contextified text returned for the result. Its size follows n_contextify.

Example: Demand for accelerated computing...

response[].semanticsobject

Semantic retrieval metadata.

Example: { "similarity": 0.9821 }

response[].semantics.similaritynumber

Semantic similarity score for the result. Use it for ranking and thresholding, not as a probability.

Example: 0.9821

query.instructionstring

Instruction produced from the agent's planning process.

Example: Compare semiconductor AI infrastructure investment.

query.expansionsstring[]

Effective expansions generated and used by the agent.

Example: ["GPU demand", "data-center capex"]

Responses and errors

HTTP

200Request succeeded. The response body is shown in the panel on the right.

400invalid_request — The request is syntactically valid JSON but a value, date, filter, or combination of fields is invalid.

401unauthorized — The required API key or Bearer credential is missing or invalid.

422validation_error — The request shape is understood but one or more values fail validation.

429rate_limited — The request exceeded the account or public-window rate limit. Respect Retry-After when supplied.

502upstream_error — An upstream retrieval service failed while processing the request.

504upstream_timeout — An upstream retrieval service did not respond within the request timeout.