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Documentation Index

Fetch the complete documentation index at: https://docs.clipping.cc/llms.txt

Use this file to discover all available pages before exploring further.

Search runs semantically (by meaning, not keywords) over the embedded content in your library — transcripts and workflow documents. 
curl "https://api.clipping.cc/v1/search?q=what%20did%20they%20say%20about%20pricing&top_k=10" \
  -H "Authorization: Bearer ck_live_…"

{
  "q": "what did they say about pricing",
  "count": 3,
  "hits": [
    {
      "chunk_id": "…",
      "score": 0.82,
      "item_id": "itm_…",
      "source_type": "transcript",
      "text": "…the pricing tier starts at…",
      "start_seconds": 142.0,
      "end_seconds": 158.5,
      "collection_ids": ["col_…"]
    }
  ]
}
Each hit points back to its item_id (and start_seconds for video transcripts, so you can deep-link into the moment).

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Narrowing

ParamEffect
qthe query (required)
top_kmax results (default 10)
collection_idrestrict to one collection
reporter_idrestrict to one reporter’s documents
item_idrestrict to one item
source_typee.g. transcript vs document kinds

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What’s searchable

Only embedded content is indexed. Make content searchable by:
Search embeds your query on each call, so it costs a bit more than a plain read (0.005 coin).

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Tag cloud

For a lighter, faceted view of a library slice, GET /v1/tags?collection_id=… (or ?item_id=…) returns the prominent tags — useful for navigation UIs.