> ## Documentation Index
> Fetch the complete documentation index at: https://docs.creatordb.app/llms.txt
> Use this file to discover all available pages before exploring further.
# Examples and Recipes for CreatorDB Agentic Skills
> A collection of examples and recipes for using CreatorDB agentic skills to call the CreatorDB API and retrieve creators or sponsoring brand data.
Make sure you have installed the CreatorDB skills onto your device. For details, see [Setting up CreatorDB Agentic Skills](/mcp-server/setting-up-creatordb-agentic-skills).
* You may be asked to provide your CreatorDB API key the first time you run a query with a skill. This is required for authentication when Claude Code calls the CreatorDB API.
* Check the [CreatorDB API documentation](https://docs.creatordb.app/api-reference) for details on the available endpoints, request parameters, and response formats to better understand how to structure your queries and interpret the results.
* Check the API usage and pricing details to understand the cost implications of your queries and manage your credits effectively. For details, see [API Credit Usage](https://docs.creatordb.app/api-v3/api-credit-usage).
Once you have installed the CreatorDB skills, you can start using them to call the CreatorDB API through Claude Code. The CreatorDB skills are designed to be user-friendly and interactive. When you run a query, follow the on-screen instructions to provide any additional information if needed. Claude Code will then use the appropriate skill to call the CreatorDB API and retrieve the requested data. Here are some examples of how to use the skills:
Responses below are illustrative reconstructions, not verbatim terminal output — exact wording, table layout, and credit numbers will vary across runs.
## Example 1: Check your account balance
To check your CreatorDB account balance, you can use the `account` skill. For example, you can prompt Claude Code with the following query:
```text theme={null}
What is my current CreatorDB account balance and API usage?
```
Claude Code will then use the `account` skill to call the CreatorDB API and retrieve your account information.
Here's your CreatorDB account snapshot.
**Balance**
* Credits remaining: 989,923
* This `/usage` call cost 0 credits (it's the `getApiUsage` op, which is free for you).
**Activity (last 7 days)**
| Date | Requests | Credits |
| ---------- | --------: | --------: |
| 2026-04-27 | 1 | 10 |
| 2026-04-28 | 270 | 2,465 |
| 2026-04-29 | 753 | 5,177 |
| 2026-04-30 | 326 | 2,074 |
| 2026-05-04 | 1 | 0 |
| **Total** | **1,351** | **9,726** |
Days 5/1–5/3 had no activity (omitted because the API doesn't return zero-usage days).
**Where credits are going**
Three contact-and-audience endpoints account for 74% of spend:
| Endpoint | Requests | Credits | Share |
| ------------------------- | -------: | ------: | ----: |
| `getYoutubeContact` | 359 | 5,385 | 55.4% |
| `getInstagramContact` | 73 | 1,095 | 11.3% |
| `getYoutubeAudience` | 74 | 740 | 7.6% |
| `getYoutubeProfile` | 343 | 686 | 7.1% |
| `getYoutubeSponsorship` | 104 | 520 | 5.3% |
| `getYoutubeContentDetail` | 173 | 519 | 5.3% |
**Platform mix**
* YouTube: 7,946 cr (81.7%)
* Instagram: 1,376 cr (14.1%)
* Sponsor endpoints: 404 cr (4.2%)
* TikTok: 0
## Example 2: Search for a specific creator
To search for a specific creator, you can use the `creator-search` skill. For example, to find information about the YouTube creator "PewDiePie", you can prompt Claude Code with the following query:
```text theme={null}
Look up PewDiePie's profile details and related accounts.
```
Claude Code will then use the `creator-search` skill to call the CreatorDB API.
| Field | Value |
| -------------------- | --------------------------- |
| Display name | PewDiePie |
| Handle | @pewdiepie |
| Channel ID | UC-lHJZR3Gqxm24\_Vd\_AJ5Yw |
| Verified | ✅ |
| Subscribers | 110,000,000 |
| Total uploads | 4,661 |
| Country (per CDB) | JPN (he relocated to Japan) |
| Main language | English |
| Has sponsors | Yes |
| Members-only content | No |
| Last published | 2026-04-23 |
| DB last updated | 2026-04-29 (fresh) |
| Bio | "I make videos." |
* Category mix: Gaming 51.5% · Entertainment 48.3% · People & Blogs 0.2%
* Topics: social-media comedy, variety gaming, vlogs, memes
* Niches: meme/gaming, Clash of Clans, Reddit reactions, art/drawing, Japan, KSI-related, fitness, "pewdiepie" niche (eponymous)
* Subscriber growth (7d/30d/90d): all flat at 0 — channel has plateaued at the 110M ceiling
* Recent hashtags hint at sponsors: #ad, #partner, #shopad, #clashofclans, #clashfornature, #gfuel, #honor20pro — Clash of Clans, G FUEL, Honor (Huawei sub-brand) all visible
* Instagram: @pewdiepie
* TikTok: @pewdiepie
* Twitch: pewdiepie
| Format | CPM range (low/raw/high) | Per-video cost (low/raw/high) |
| --------------- | ------------------------ | ----------------------------- |
| Long-form video | | |
| | | Shorts |
The full relatedCreators list contains 323 channel IDs, ranked by CreatorDB's similarity model. Here's the top 15 with names attached:
| # | Creator | Handle | Subs | Country |
| -- | --------------------------------- | ----------------- | ------ | ------- |
| 1 | Markiplier | @markiplier | 38.6M | USA |
| 2 | penguinz0 (Charlie/MoistCr1TiKaL) | @penguinz0 | 18.0M | — |
| 3 | Veritasium | @veritasium | 20.7M | USA |
| 4 | Doctor Mike | @doctormike | 14.8M | USA |
| 5 | The Daily Show | @thedailyshow | 13.8M | USA |
| 6 | LastWeekTonight | @lastweektonight | 10.1M | — |
| 7 | jacksepticeye | @jacksepticeye | 31.2M | IRL |
| 8 | Jimmy Kimmel Live | @jimmykimmellive | 22.0M | USA |
| 9 | MrBeast Gaming | @mrbeastgaming | 56.0M | USA |
| 10 | MrBeast | @mrbeast | 480.0M | USA |
| 11 | CinnamonToastKen | @cinnamontoastken | 4.8M | USA |
| 12 | Ryan Trahan | @ryan | 22.9M | USA |
| 13 | Chat History | @chathistory | 1.0M | USA |
| 14 | Technoblade | @technoblade | 22.1M | USA |
| 15 | The Spiffing Brit | @thespiffingbrit | 4.4M | GBR |
* Top of the related list = closest co-watch / similar-audience peers. The first three (Markiplier, penguinz0, Veritasium) reflect PewDiePie's actual audience overlap — gaming-comedy + science creators his viewers also subscribe to.
* MrBeast and MrBeast Gaming sitting at #9–10 makes sense given collab history and audience overlap.
* Late-night TV brands (Daily Show, Last Week Tonight, Jimmy Kimmel) appearing high in the related list is interesting — likely reflects English-speaking general-entertainment co-viewing, not direct topical similarity.
* Technoblade (#14) — note this is a memorial channel; the creator passed in 2022 but the channel remains active.
* The full 323-creator list is available if you want the long tail (would cost \~616 cr to enrich them all to names; happy to enrich any specific batch you point at).
Credits used this turn: 32 (1 PewDiePie profile + 15 related profiles + 1 prior balance probe was already counted). Remaining: \~991,777.
## Example 3: Search for creators that meet specific conditions
To search for creators based on specific criteria, you can use the `creator-search` skill. For example, to find Instagram creators in the US "gaming" category with more than 1 million followers and high engagement rates, you can prompt Claude Code with the following query:
```text theme={null}
Find me the top 10 US gaming Instagrammers with at least 1M followers and high engagement rates
```
Claude Code will then use the `creator-search` skill to call the CreatorDB API.
Here's the ranked top 10. Worth flagging some quality caveats below.
| # | Handle | Display | IG Category | Followers | ReelsER |
| -- | ------------------- | -------------------- | --------------- | --------: | ------: |
| 1 | @nihaachuu | Niki | Video creator | 1,414,162 | 6.98% |
| 2 | @nrggram | NRG | E-sports team | 1,590,020 | 4.62% |
| 3 | @thepointerbrothers | the pointer brothers | Digital creator | 2,510,184 | 4.60% |
| 4 | @shroud | Michael Grzesiek | Public figure | 1,258,981 | 4.20% |
| 5 | @thesketchreal | Sketch | Digital creator | 1,716,511 | 4.16% |
| 6 | @nadeshot | Matthew Haag | Digital creator | 1,161,500 | 4.06% |
| 7 | @annashumatee | anna | Gamer | 1,465,704 | 3.03% |
| 8 | @ronnie2k | Ronnie Singh | Public figure | 1,098,515 | 3.01% |
| 9 | @lolesports | LoL Esports | ESPORTS\_LEAGUE | 1,838,146 | 2.69% |
| 10 | @g2esports | G2 Esports | ESPORTS\_TEAM | 1,378,395 | 2.57% |
* Confirmed core-gaming creators (8 of 10): shroud, Sketch, Nadeshot, ronnie2k (NBA 2K), and the four esports orgs (NRG, LoL Esports, G2, plus the "Gamer"-categorized annashumatee). These are unambiguously gaming.
* Verify before outreach (2 of 10):
* \#1 @nihaachuu (6.98% ER) — IG category is "Video creator", not "Gamer". She showed up in the gaming-niches search but her primary content is modeling/lifestyle, not gameplay. ER is genuinely high but she may not be a fit if you specifically want gaming-content creators.
* \#3 @thepointerbrothers — also "Digital creator". They make NBA / sports-comedy content; appeared here because they used #gameday / #gaming hashtags. Almost certainly not a gaming creator.
* Industry benchmarks: \<0.5% is typical for mega-IG accounts, 1–3% is healthy mid-tier, >5% is exceptional. The whole list lands in the healthy-to-exceptional range, which is plausible for gaming-niche IG (smaller, more loyal audiences).
Instagram's gaming discovery in CDB is hashtag-driven and noisy:
* The id\_gaming\_All niche pulled 23K creators including HOT 97, Demi Lovato, Sanrio, Matthew Lillard.
* NLS for the same query surfaced Zendaya, Cardi B, Rihanna alongside real gaming creators.
* The IG category field (e.g., "ESPORTS\_TEAM", "Gamer") is more reliable than niches but only \~5–10% of creators have a gaming-specific value.
So this list is the result of: niche-search candidates → manual filter to gaming-clear handles → enrich with `/instagram/performance` for actual ER → rank. If you need a strictly-vetted list, drop @nihaachuu and @thepointerbrothers and pull the next two candidates (@dakotaz at 1.49% ER and a couple from a wider search).
Search probes + 12 × profile + 12 × performance ≈ \~60 cr total. Remaining: \~988,200.
## Example 4: Build an outreach list end-to-end
To create an outreach list of potential creator partners for a campaign, you can use a combination of the `creator-search` and `creator-enrichment` skills. For example, to find 50 beauty TikTokers with more than 500,000 subscribers in the US with high engagement rates and retrieve their contact information, you can prompt Claude Code with the following query:
```text theme={null}
Find the top 50 beauty TikTok creators with more than 500,000 subscribers in the US with high engagement rates and retrieve their contact information.
```
Claude Code will then use the `creator-search` and `creator-enrichment` skills to call the CreatorDB API.
| # | Handle | Followers | ER | Email | Source |
| -- | ------------------------ | --------: | -----: | ----------------------------------------------------------------------------------- | ------- |
| 1 | @cannolifamily | 1.00M | 97.05% | — | none |
| 2 | @michaelahallmark1 | 1.20M | 34.00% | — | none |
| 3 | @elisapur | 1.00M | 26.78% | [elisapurisic20@gmail.com](mailto:elisapurisic20@gmail.com) | bio |
| 4 | @theeglamnaija | 1.30M | 26.61% | [naijelee@creatorcollectivetalent.com](mailto:naijelee@creatorcollectivetalent.com) | bio |
| 5 | @ivy.eve.scarlet | 1.70M | 23.48% | — | none |
| 6 | @ziggityler | 1.50M | 22.96% | [ziggisinbox@gmail.com](mailto:ziggisinbox@gmail.com) | contact |
| 7 | @queen.olu | 692K | 22.78% | [queenolu@thedigitaldept.com](mailto:queenolu@thedigitaldept.com) | bio |
| 8 | @cutiepiesensei | 1.00M | 22.62% | — | none |
| 9 | @soulbangs224 | 717K | 22.16% | [contact@soulbangs224.com](mailto:contact@soulbangs224.com) | contact |
| 10 | @timmyst.jean | 718K | 21.80% | [timmystjean@dulcedo.com](mailto:timmystjean@dulcedo.com) | bio |
| 11 | @mayzeson | 628K | 21.26% | — | none |
| 12 | @jayrianicole | 831K | 21.20% | [Jayria@kensingtongrey.co](mailto:Jayria@kensingtongrey.co) | bio |
| 13 | @mel\_loves\_her\_cat | 586K | 20.91% | — | none |
| 14 | @chazonator | 1.20M | 20.87% | [chazonator@outlook.com](mailto:chazonator@outlook.com) | contact |
| 15 | @nayaloyden4 | 849K | 20.87% | [nayasimone@dulcedo.com](mailto:nayasimone@dulcedo.com) | bio |
| 16 | @cloeawesomeness | 925K | 20.85% | [kaila@atggroup.io](mailto:kaila@atggroup.io) | bio |
| 17 | @allyduhrey | 531K | 20.73% | [allyp19@gmail.com](mailto:allyp19@gmail.com) | bio |
| 18 | @keeksandkooks | 536K | 20.54% | — | none |
| 19 | @officialchristianwalk1r | 1.80M | 20.54% | [christianwalkercontact@gmail.com](mailto:christianwalkercontact@gmail.com) | bio |
| 20 | @still.bad.decisions | 1.40M | 20.51% | — | none |
Rows 21–50 are saved in `/{YOUR WORKING DIRECTORY}/{FILENAME}.csv` with full bios, niches, and verification flags. Notable agency contacts in the long tail: kensingtongrey, dulcedo, undercurrent.net, viralnationtalent, fixated, lucky8collective, thedigitalbrandarchitects.
1. The ER values are TikTok-formula (likes + comments + shares) / followers, which runs noticeably higher than YouTube/Instagram ER. #1 @cannolifamily at 97.05% is almost certainly a recent-window artifact (one viral video pulling the rolling average up); double-check before reporting it as a sustained metric. #2 @michaelahallmark1 at 34% is also extreme — verify content fit (her bio mentions "MakeJesusKnown" hashtags, may be more lifestyle/faith than beauty).
2. Niche-tag noise: The TikTok beauty niches are hashtag-driven, and several handles in the list don't clearly skew beauty:
* @still.bad.decisions (#20) — bio says "TheCarGirl BackUp Cars, corgs, and complaining"
* @dunknatachai (#34, 3.2M) — Thai actor (Disney/GMMTV credits)
* @sway\_bhatia1 (#31) — actress
* @christwodafur (#38, 3.1M) — Star Wars cosplay
* Some have very generic bios suggesting general lifestyle content rather than beauty
The strongly-beauty-confirmed handles are the ones with agency emails (kensingtongrey, dulcedo, etc.) and bio mentions of makeup/skincare. If you want a strictly beauty-only roster, filter the CSV to rows with beauty-keyword bios or pull `/tiktok/sponsorship` to confirm beauty-brand work history.
| Metric | Value |
| ----------------------- | -------- |
| Rows processed | 50 / 50 |
| Failed rows | 0 |
| Rows with ≥1 email | 37 (74%) |
| Bio-email hits (free) | 27 |
| `/tiktok/contact` calls | 23 |
| Rows with no email | 13 |
| Step | Cost |
| -------------------------- | ---------: |
| `/tiktok/search` × 1 | 1 cr |
| `/tiktok/profile` × 50 | 100 cr |
| `/tiktok/contact` × 23 | 345 cr |
| `/tiktok/performance` × 50 | 100 cr |
| **Total** | **546 cr** |
Bio-first contact approach saved \~405 cr vs. blindly calling `/contact` on all 50. Remaining: \~987,650.
Examples 5a-5c each show a different cut of the `brand-sponsorship` skill: known brand → roster (5), vertical → brands (6), brand → spend estimate (7).
## Example 5: Brand and sponsorship analysis
The following examples show how to use the `brand-sponsorship` skill to analyze a brand's sponsored creator roster, identify which brands are active in a specific vertical, and estimate a brand's monthly spend on creator partnerships.
### 5a: Verify a brand's sponsored creator roster
To verify a brand's sponsored creator roster, you can use the `brand-sponsorship` skill. For example, to find out which creators are sponsored by Adidas, you can prompt Claude Code with the following query:
```text theme={null}
List all creators sponsored by Adidas.
```
Claude Code will then use the `brand-sponsorship` skill to call the CreatorDB API.
Total: 432 creators — 405 YouTube + 27 Instagram. Saved to `/{YOUR WORKING DIRECTORY}/{FILENAME}.csv`.
| Platform | Creators | Notes |
| --------- | -------: | ----------------------------------------------- |
| YouTube | 405 | Long tail of football/sports niche channels |
| Instagram | 27 | Mostly athlete partnerships, much sparser index |
Top 10 countries by creator count: USA 69 · ESP 25 · JPN 23 · GBR 17 · FRA 17 · THA 17 · POL 16 · KOR 16 · BRA 15 · DEU 15
True global program — not US-centric. Spain, Japan, and Thailand are notably high (football market + Asian apparel push).
| Creator | Country | Subs | Placements | Last |
| ------------------------- | ------- | ----- | ---------: | ---------- |
| Fotbollsmorgon | SWE | 40K | 25 | 2026-04-04 |
| Canal Camisas e Chuteiras | BRA | 187K | 19 | 2026-03-02 |
| John Cincola Pickleball | USA | 80K | 19 | 2026-02-26 |
| FC AFKICKEN | NLD | 50K | 18 | 2025-11-07 |
| Soccer Reviews For You | USA | 836K | 16 | 2025-10-01 |
| futbolmania | ESP | 60K | 15 | 2025-10-02 |
| Best Buy Soccer | USA | \<10K | 14 | 2026-01-15 |
| 골챔 (Golchamp) | KOR | 13K | 13 | 2025-12-03 |
| SUPERGAANDE | NLD | 887K | 11 | 2025-05-28 |
| Futbolistas | MEX | 871K | 11 | 2025-08-20 |
Pattern: Adidas leans heavily on mid-tail soccer/football review channels for repeat partnerships (boots, kits, gear reviews) rather than mega-creators. Volume of placements doesn't track follower count — Fotbollsmorgon has 25 placements at just 40K subs, while 12.9M-sub J Jai Pan has only 1.
12.9M (J Jai Pan, THA) · 8.57M (loveliveserve, USA) · 6.91M (Complex, USA) · 5.40M (Unisport, 7 placements — also a heavy partner) · 5.40M (Blowek, POL) · 2.89M (DAZN Football) · 2.32M (adidas' own channel — interesting that it shows up as a "sponsored creator" of itself, treat as a self-reference noise row).
Only 27 IG creators indexed. Top by reach: N'Golo Kanté (16.5M, 2021), Trinity Rodman (750K, 2026-01), Melanie Leupolz (290K, 2024). Most have just 1 placement and many entries are very small accounts (\<50K). The IG sponsored-content index for Adidas appears thin compared to YouTube.
* adidas channel itself appears in the YouTube list (USA, 2.32M subs, 1 placement). That's the brand's own channel — likely a self-tag from a user-generated content collab. Filter it out for clean creator-side analysis.
* CreatorDB sponsorship detection is heuristic — undisclosed paid partnerships and creators using non-standard tags are missed. Real Adidas roster is likely larger.
* The 27 Instagram results are a suspiciously low count for a brand of Adidas's scale — IG sponsorship indexing in CDB is generally less complete than YouTube's. If IG is critical, treat this list as partial.
| Step | Credits |
| --------------------------------------- | ------: |
| `/sponsor/information` | 2 |
| `/sponsor/creators` (YouTube ×5 pages) | 125 |
| `/sponsor/creators` (Instagram ×1 page) | 25 |
| **Total** | **152** |
Remaining: \~990,189.
CSV columns: `platform`, `creatorId`, `displayName`, `country`, `followers`, `sponsoredCount`, `lastSponsoredDate`, `avgRecentSponsoredEngagementRate`, `topics`, `niches`. Open from your working directory with Numbers or Sheets.
### 5b: Retrieve brands sponsoring creators
To retrieve data on brands sponsoring creators, you can use the `brand-sponsorship` skill. For example, to find the top 10 brands sponsoring US gaming YouTubers, you can prompt Claude Code with the following query:
```text theme={null}
Find the top 10 brands sponsoring US gaming YouTubers.
```
Claude Code will then use the `brand-sponsorship` skill to call the CreatorDB API.
Based on a sample of 50 US gaming YouTubers (1M+ subs, English-speaking, active), aggregating who sponsors how many distinct creators.
| # | Brand | Vertical | Creators sponsored | Total placements | Example creators |
| -- | ---------------- | ------------------ | -----------------: | ---------------: | ----------------------------------------------------------- |
| 1 | Epic Games | Game publisher | 6 | 9 | MrBeast Gaming, PrestonPlayz, ItsFunneh, Flamingo, SypherPK |
| 2 | Ubisoft | Game publisher | 4 | 15 | CoryxKenshin, VanossGaming, theRadBrad, The Game Theorists |
| 3 | Marvel Rivals | Game (NetEase) | 4 | 5 | H2ODelirious, VanossGaming, ItsFunneh, The Game Theorists |
| 4 | Intel | Hardware | 3 | 6 | MrBeast Gaming, SypherPK, Caylus |
| 5 | AFK Journey | Game (Farlight) | 3 | 4 | VanossGaming, The Game Theorists, Caylus |
| 6 | Crystal of Atlan | Game (NVS/NetEase) | 3 | 3 | VanossGaming, The Game Theorists, Caylus |
| 7 | Sony | Hardware/Publisher | 3 | 3 | VanossGaming, theRadBrad, SypherPK |
| 8 | War Thunder | Game (Gaijin) | 3 | 3 | KreekCraft, VuxVux, Caylus |
| 9 | Chime | Fintech | 2 | 8 | UnspeakableReacts, The Game Theorists |
| 10 | NordVPN | Cybersecurity | 2 | 6 | Markiplier, The Game Theorists |
* Game publishers and individual game titles dominate — 7 of the top 10 are gaming companies promoting their own games. Epic Games leads on roster reach (Fortnite-related promos especially), Ubisoft leads on placement volume (15 placements across 4 creators = repeat partnerships).
* Mobile gacha / F2P MMOs are aggressive sponsors — Marvel Rivals, AFK Journey, Crystal of Atlan, War Thunder all rely heavily on creator marketing for user acquisition. NetEase appears under multiple titles (Marvel Rivals + Crystal of Atlan).
* Non-gaming partners: Chime (banking) and NordVPN (VPN) — the two evergreen "every creator" sponsors. Chime's 8 placements across just 2 creators shows it's a high-frequency repeat partner where it does land.
* Hardware tier: Intel (3) and Alienware (2, just outside top 10) — the consistent PC-hardware pair.
* Just outside top 10: Alienware, 2K, Lurkit (a creator-marketing platform itself), GeoGuessr, my.games — all at 2 creators each.
* Sample of 50 creators, sorted by subscribers descending — top-of-funnel skew. Smaller channels in the long tail may show different sponsor patterns.
* CreatorDB sponsorship detection is heuristic (disclosure tags, hashtag conventions). Undisclosed paid placements get missed; the actual ranking could shift slightly.
* /youtube/sponsorship returns up to \~20 most recent sponsored uploads per creator, not lifetime — so very old partnerships won't appear.
* Tie-breaking near the cut: brands ranked #8–10 all have only 2–3 creators in the sample. A larger sample (e.g., 200 creators) would give more robust ranks below the top 5.
* Expand the sample to 200 creators (\~1,000 cr more) for tighter ranking below the top 5
* Filter to a specific gaming sub-niche (e.g., FPS, Roblox, Minecraft) using the niches filter
* Cross-reference with /sponsor/summary for the top brands to see their estimated 30-day spend on YouTube overall
* Get the audience demographics of each top brand's sponsored pool with /sponsor/audience
Credits used this turn: \~251 (1 search + 50 sponsorship). Remaining: \~991,558.
### 5c: Estimate brand spend on sponsoring creators
To retrieve data on a brand's spend on sponsoring activities, you can use the `brand-sponsorship` skill. For example, to find Nvidia's latest sponsoring activities, you can prompt Claude Code with the following query:
```text theme={null}
Estimate Nvidia's influencer marketing spend over the last 30 days
```
Claude Code will then use the `brand-sponsorship` skill to call the CreatorDB API.
\~\$24,448 USD (YouTube only; CreatorDB model estimate)
| Metric | Value |
| ---------------------------- | --------- |
| Sponsored content (30d) | 22 pieces |
| Views on that content (30d) | 1,474,969 |
| Estimated CPM (30d) | \$16.58 |
| Estimated CPE (30d) | \$0.51 |
| Avg engagement rate | 3.93% |
| 7d spend / 90d spend | |
| 30d view growth vs prior 30d | −5.3% |
| 30d engagement growth | −2.3% |
* The 90-day total is ~~\$249K, so the last 30 days (~~\$24K) is well below the trailing pace — Nvidia's sponsored YouTube cadence has cooled meaningfully. The \$0 in the last 7 days reinforces that (no detected sponsored placements in the most recent week).
* Engagement and views are both negative on the 30-day growth window — fewer placements and softer per-piece performance.
* Instagram is excluded. Nvidia has 0 sponsored creators indexed on Instagram, and `/sponsor/summary` doesn't model IG spend regardless — so this number is effectively the full picture for the platforms CreatorDB tracks (YouTube + IG), but it does not include TikTok or other channels.
* These are modeled estimates, not booked spend — useful for benchmarking and trend, not for citing as Nvidia's actual budget.
* Engagement rate here uses (likes + comments) / views, different from creator-side engagement formulas — don't compare directly to creator search filters.
Credits used: 25 · Remaining: 991,910
## Example 6: Transcribe a video for content analysis
To transcribe a video for content analysis, you can use the `content-analysis` skill. For example, to transcribe a creator's video to find out if they mention a specific brand, you can use the following prompt:
```text theme={null}
Transcribe MrBeast's most recent YouTube video and find any brand mentions in it.
```
Claude Code will then use the `content-analysis` skill to call the CreatorDB API.
**The transcript availability situation**
Of MrBeast's most recent uploads:
| Date | ID | Type | Title | Subtitle status |
| ---------- | ----------- | --------- | --------------------------------------------- | --------------- |
| 2026-04-29 | EdT5Z16Y5WE | Short | Would Your Dog Pick \$10,000 or Steak? | ❌ none indexed |
| 2026-04-28 | ScjQAcbA9e4 | Short | Important Announcement From The Grocery Store | ❌ none |
| 2026-04-27 | hRBpDdWbUpI | Short | Can My Fiancée Lift Me? | ❌ none |
| 2026-04-24 | pzxtGL9kzPs | Short | Try Not To Get Slimed | ✅ auto English |
| 2026-04-21 | yy-Nt0dRhNI | Short | Winner Picks Our Honeymoon | ✅ auto English |
| 2026-04-18 | zRtGL0-5rg4 | Long-form | Last To Leave Grocery Store, Wins \$250,000 | ❌ still none |
The actual most-recent long-form video still hasn't had subtitles ingested by CreatorDB.
**Transcripts of the two most-recent transcribable videos**
`pzxtGL9kzPs` "Try Not To Get Slimed" (2026-04-24, \~30s)
> "OH, GOSH. WHAT IS THAT? WOAH, WOAH, WOAH, WHAT? ARE YOU DONE? YEAH, GO AWAY. THAT'S DISGUSTING. ... OH, IT FEELS SO NASTY, BRO. KEEP POURING. ALL RIGHT, HERE WE GO. ... IT'S SO BUBBLY."
Brand mentions: none. Stunt reaction video, no dialogue beyond exclamations.
`yy-Nt0dRhNI` "Winner Picks Our Honeymoon" (2026-04-21, \~45s)
> "Winner picks our honeymoon. Okay, you just got to get more balls in than the other person ... I want to go on an island. ... Right after we get married WITHOUT MY PHONE, BABE. ... I want uh to go to space. ... Hey, Jeff Bezos, you know that like rocket that close your ears that looks kind of like a \[...] that goes to space. I would love to go."
| Mention | Context | Type |
| --------------------- | -------------------------------------------------------------------------------------------------------------- | -------------------------- |
| Jeff Bezos | Direct address asking for a Blue Origin ride | Founder reference |
| Blue Origin (implied) | "rocket that close your ears... goes to space" — unmistakable reference to New Shepard's well-memed silhouette | Indirect product reference |
That's the entire brand surface area in these two shorts. No Feastables, no sponsor reads, no product placements.
| Step | Credits |
| --------------------------------- | ------: |
| `/youtube/content-detail` | 3 |
| `/youtube/subtitles/meta` × 6 | 6 |
| `/youtube/subtitles/download` × 2 | 2 |
| **Total** | **11** |
Remaining: \~990,178.
## Example 7: Submit and enrich creator list in CSV format
To submit and enrich a creator list in CSV format, you can use the `creator-csv-workflow` skill. For example, if you have a CSV file with a list of YouTube creator channel IDs and you want to enrich it with additional data from CreatorDB, you can follow these steps:
a. Obtain YouTube creator channel IDs through any of the following methods:
* Call the CreatorDB API.
You can call the CreatorDB API using the `creator-search` skill in Claude Code to find creators based on specific criteria (e.g., niche, subscriber count, location). This will return a list of creator profiles, including their channel IDs, which you can then export to a CSV file for enrichment. For details, see Examples 2 and 3 in this guide on how to use the `creator-search` skill effectively.
* Search social media platforms, such as YouTube.
* Use your own database.
* Purchase a list from a data provider.
b. Ensure that the channel IDs are in a CSV format with a header row (e.g., `channelId`).
Prompt Claude Code with the following query, replacing `path/to/your/creators.csv` with the actual path to your CSV file:
```text theme={null}
Enrich the creator list in this CSV file with additional data from CreatorDB: path/to/your/creators.csv
```
Claude Code will then use the `creator-csv-workflow` and `creator-enrichment` skills to call the CreatorDB API and enrich your creator list with additional data such as subscriber count, engagement metrics, audience demographics, and more. The final output should be an enriched CSV file with the new data columns added, which you can use for further analysis or outreach.
For example, if your original CSV had a `channelId` column, the enriched CSV might include additional columns like `displayName`, `totalSubscribers`, `engagementRate`, `audienceAgeRange`, etc., depending on the data available for each creator in CreatorDB.
The following is an example of the messages returned for a successful enrichment of a list of 50 gaming YouTubers:
**Results**
| Metric | Value |
| --------------------- | -------: |
| Rows processed | 50 / 50 |
| Failed rows | 0 |
| Rows with ≥1 email | 37 (74%) |
| Bio-email hits (free) | 11 |
| `/contact` calls made | 39 |
| Total credits used | 1,185 |
Bio-first saved \~210 cr vs always calling `/contact` (would've been 50 × 27 = 1,350).
**Output**
* Enriched data: `/{YOUR WORKING DIRECTORY}/{FILENAME}.csv` — 50 rows × 40 columns (profile + audience demographics + emails + `_row_id` / `email_source` / `_credits_used` / `_error` bookkeeping).
* Summary: `/{YOUR WORKING DIRECTORY}/{FILENAME}.csv` — totals + failed-row list (empty).
* Script: `/{YOUR WORKING DIRECTORY}/{SCRIPTNAME}.py` (kept, in case you want to re-run or adapt).
13 channels with no email found.
## Next steps and resources
For further details about the CreatorDB API endpoints used in these examples and costs, please refer to the following documentation:
* [CreatorDB API Documentation](https://docs.creatordb.app/api-reference/)
* [API Credit Usage](https://docs.creatordb.app/api-v3/api-credit-usage)
* [Claude Code Documentation](https://claude.ai/docs/code)
* [CreatorDB Pricing](https://creatordb.app/pricing)