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API & MCP/Data coverage

Data coverage

The honest numbers: how often analysis succeeds, what analysis_status means, and what the niche catalogue does and does not carry.

Updated Sep 9, 2026·4 min read

Analysis success rate: ~89–97% per month

Measured across 2026: the share of catalog rows that reach a completed analysis has run between roughly 89% and 97% in any given month — comparable to the ~94% figure the leading competitor in this space publishes. Not every analysis succeeds; the pipeline can fail on a given video (an unreachable URL, a downstream processing error) or leave it pending. analyze_tiktok_video is safe to retry — a video that already holds a catalog slot from a prior failed attempt does not spend a second one.

What analysis_status means

  • complete — analyzed under the current schema; every field group (hook, timing, scenes, transcript, ...) is present.
  • partial — analyzed under an older schema, before June 2026. The missing array names which fields the pipeline didn't yet extract at the time — not a defect specific to that video. See below.
  • pending — a job is still running. Poll again.
  • failed — the pipeline hit an error on this video. Check the accompanying error/failure detail.
  • not_analyzed — nobody has ever requested analysis for this video.
partial and failed are different things and the API is careful to say which — an older schema is not a broken video, and treating the two the same in a client would tell your users something untrue.

Scenes, timing and transcript: 100% only since June 2026

Coverage is uneven by vintage. Scene-by-scene breakdown, hook timing and full transcripts are present on effectively 100% of rows analyzed since June 2026, and sparse on almost everything analyzed before it (well under 15% for videos from early 2026) — those fields simply weren't extracted by the pipeline that far back. A request for scene timing on a pre-June-2026 video returns an empty array with analysis_status: "partial" and missing naming what's absent — check that field before assuming the video had no notable scenes.

The niche catalogue carries no per-video analysis

Measured 2026-09-06: 26,745 rows in the niche catalogue, of which only 31 (0.1%) have ever reached full AI analysis. browse_niche_catalog (GET /v1/niches) and GET /v1/niches/{id}/videos return thumbnails, engagement stats and a multiplier ranking — never a hook type, scene breakdown or transcript. To get real analysis on a catalogue video, call analyze_tiktok_video on it directly, which spends a standing catalog slot exactly like any other video (see Rate limits & quotas).

The intended workflow for an agent is: create_niche or browse_niche_catalog to find ranked candidates by multiplier, then analyze_tiktok_video on the best one for the full breakdown. Analyzing every result in a catalogue page can burn 10% of a Creator workspace's lifetime catalog in a single loop — be deliberate about which videos are worth the slot.
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