AI Discovery · Audit

Audited

Atomic Habits

by James Clear

74of 100

Partial discovery

AI answers vary run to run, so treat this as an indicative band, not a precise mark — the verdict and the fixes below are what matter.

In the conversation.

Some engines surface your book reliably. Others miss it. The chapters below show which, and where to focus.

At the balanced depth · you are bestseller-tiermedian ~18top 10% ~42bestseller ~70+

Dual score · SKU vs Topic

Your book (SKU)

74 / 100

Your subject

74 / 100

AI engines know your book and its subject well — focus shifts to defending position.

SKU score = book mentioned by name (strict). Topic score = response acknowledged your subject (looser — counts author mentions and topic-word overlap). Headline score uses the SKU number.

Profile

Four axes. One picture.

The score breaks into four things AI can do (or can't) with your book.

Known-title recall

20 /25

AI recalls the book when named.

Recommendation fit

14 /25

Surfaces when readers describe the need.

Market authority

19 /25

In the genre-listicle / canon pool.

List position

21 /25

Where it lands in ranked lists.

What this looks like

A reader asks AI:

Best books about self-help productivity published in the last 12 months — give me 10.

ChatGPT replies

“You should read Deep Work.”

— not Atomic Habits.

What this would cost you otherwise

  • Manual visibility check across 5 AI engines, incl. Rufus (analyst)£300–600
  • A dedicated AI-visibility SaaS seat (Profound, Peec, etc.)£99–499/mo
  • Verbatim AI answers + citation-source forensics£150–300
  • Comp-title / competing-author analysis£150–300
  • Paste-ready blurb + metadata rewrite (KDP / A+)£150–300
  • Prioritised fix-it action plan + re-check£200–400
Comparable total£950–2,400+

Surfio does it across 5 engines incl. Amazon Rufus in ~4 minutes — £29.99.

What AI says

We asked 5 engines, 60 prompts.

A sample of the questions, and what AI answered.

Surfaced

Best books about self-help productivity published in the last 12 months — give me 10.

Amazon Rufus mentioned "Atomic Habits".

Missed

Best books about self-help productivity published in the last 12 months — give me 10.

Gemini answered without mentioning your book.

Cited competitor

Best books about self-help productivity published in the last 12 months — give me 10.

ChatGPT cited kirkusreviews.com instead.

Where to get featured

The sources AI trusts — and which to pitch first.

AI recommends books it sees cited across these sources. This is your outreach shortlist, ranked by how likely each is to say yes — get featured here and you get recommended.

Pitchable78 domains

Book blogs, niche listicles, indie reviews — most likely to land

Aspirational5 domains

Mid-tier press, podcasts, trade — possible with a real angle

  • goodreads.com6× citedVisit
  • medium.com2× citedVisit
  • thisisnotamemo.substack.com2× citedVisit
  • bookshop.org2× citedVisit
  • sanjidakay.substack.com1× citedVisit
Out of reach8 domains

Broadsheets, network news — only with a major news hook

Was your book used to train AI?

Yes — your book was scraped.

We cross-referenced your book against datasets used to train AI models. Confirmed matches (Books3, Common Crawl) are definitive; others are a probability assessment. Informational only — not legal advice; consult a qualified lawyer before acting.

Why this matters:Anthropic settled $1.5 billion in Sept 2025 (~$3,000 per claimed title). In April 2026, NVIDIA was ordered to pay $322 million for negotiating a deal with Anna’s Archive — the umbrella shadow library that hosts most of the datasets below. Every major AI lab has at minimum scraped Common Crawl; many have used the shadow-library datasets too.
  • LibGen

    Used by: Meta (LLaMA 1/2/3), Anthropic (Claude 1/2), alleged: OpenAI

    UNKNOWN

    Book is too new or lacks Amazon listing — and Anna's Archive lookup unreachable.

    active class action — Kadrey v. Meta

    Active class action against Meta for downloading LibGen + Z-Library. If your book is in LibGen you are AUTO-ENROLLED. Action: send a copyright assertion letter (template below) and join the Authors Guild Meta list.

    Read & join →
  • Z-Library

    Used by: Meta (LLaMA 1/2/3 — confirmed in court filings)

    UNKNOWN

    Z-Library is ISBN-keyed and Anna's Archive lookup unreachable — can't confirm coverage.

    active class action — Kadrey v. Meta

    Z-Library use is part of the same Meta lawsuit. Zuckerberg personally signed off on the Z-Library downloads per unsealed internal emails.

    Read & join →
  • Books3

    Used by: EleutherAI (Pile), Meta (LLaMA-1), Bloomberg GPT

    FOUND

    CONFIRMED in Books3. Filename "Atomic Habits_ Tiny Changes, Remarkable Results 2018 - James Clear" matches your title + author in the Books3 dataset (197,000 files).

  • PiLiMi

    Used by: Anthropic (confirmed in court filings)

    UNKNOWN

    PiLiMi is a LibGen mirror. If your book is on LibGen it's probably on PiLiMi too.

    settled class action — Bartz v. Anthropic

    Anthropic SETTLED for $1.5 billion in Sept 2025 — ~$3,000 per qualifying title. Claims deadline was 30 March 2026 (past). New lawsuits expected.

    Read & join →
  • Anthropic-class

    Used by: Anthropic (Claude 1, 2)

    UNKNOWN

    The Anthropic settlement class list contains ~500k titles. We can't auto-check this yet; visit the Authors Guild search tool to verify your eligibility for the $1.5BN distribution. Claims deadline was 30 March 2026 — check now in case appeals reopen the window.

    settled class action — Bartz v. Anthropic (settled $1.5BN)

    Search the published class list directly to check eligibility. Even if claims deadline passed, document your inclusion for future related lawsuits.

    Read & join →
  • BookCorpus

    Used by: Google (BERT), OpenAI (GPT-1, GPT-2), Meta (RoBERTa)

    UNKNOWN

    Your book post-dates BookCorpus's 2015 scrape window. Lower likelihood — but Smashwords-published books from this era are well-documented in BookCorpus.

  • HathiTrust

    Used by: Anna's Archive (scraped by NVIDIA, others), Indirect AI training via Anna's Archive

    UNKNOWN

    HathiTrust scans tend to be older library titles — your book may not be covered.

  • The Pile (full)

    Used by: EleutherAI, Meta (LLaMA-1), Bloomberg GPT, many open-source LLMs

    UNKNOWN

    The Pile was assembled 2020-2021; newer books less likely. But ArXiv, PubMed, OpenSubtitles — check by content type.

  • Common Crawl

    Used by: OpenAI (all GPT models), Google (T5, Gemini, Bard), Anthropic (Claude), Meta (LLaMA, BLOOM)

    LIKELY

    Common Crawl scrapes the entire public web every 1-2 months. Your Amazon listing (including "Look Inside" excerpts), Goodreads page, author blog posts, free chapter samples, and Wikipedia entries about your book are almost certainly in Common Crawl. OpenAI, Google, and Anthropic all use Common Crawl as a primary training source.

  • Hugging Face datasets

    Used by: Any model fine-tuned on HF community datasets, Researchers, open-source LLMs

    UNKNOWN

    Books not yet listed on Amazon are less likely to be in third-party scraped collections.

  • AO3 fanfic scrape

    Used by: Unknown — community-uploaded; downstream model training unverified but likely

    UNKNOWN

    In April 2025, user "nyuuzyou" scraped 12.6 million fanfics from Archive of Our Own and uploaded to Hugging Face. If you write fanfiction, post on AO3, or have crossposted work there, you're affected. OTW is actively pursuing takedowns.

  • Wattpad / Fanfiction.net

    Used by: Naver HyperCLOVA-X (Wattpad direct), Various research scrapes

    UNKNOWN

    Wattpad (90M users, owned by Naver) and Fanfiction.net are widely scraped by both researchers and AI companies. Wattpad has cooperation with Naver's HyperCLOVA-X model. If you've published original or fan work there, it may be in training corpora.

  • Internet Archive scans

    Used by: Internet Archive (now ceased), Unknown downstream AI training

    UNKNOWN

    IA's CDL program ran until late 2024 but newer or non-ISBN books are less likely to have been scanned.

Pre-filled letters — copy & send

Copyright assertion letter to Meta

To: Meta Platforms, Inc. — Copyright Agent (copyright@meta.com)

2 June 2026

Re: Unauthorized use of copyrighted work in AI training datasets — "Atomic Habits" by James Clear

To whom it may concern,

I am the rights holder of the work titled "Atomic Habits" (the "Work"). I have reasonable grounds to believe that the Work was downloaded by Meta from LibGen, Z-Library, and/or PiLiMi — repositories that Meta has admitted (per unsealed court filings in Kadrey v. Meta) using to train its LLaMA family of large language models without permission.

I hereby:

  1. Assert my exclusive copyright in the Work.
  2. Demand that Meta cease using the Work, or any derivative thereof, in training, fine-tuning, evaluation, or operation of any AI system.
  3. Demand confirmation, in writing within 30 days, of whether the Work was downloaded by or on behalf of Meta and whether it was used in training any Meta-owned or operated model.
  4. Reserve all rights including but not limited to damages, attorneys' fees, and injunctive relief.

I do not grant any license, permission, or authorisation to use the Work for any purpose related to AI training, fine-tuning, or evaluation.

Please direct all responses to the address above.

Sincerely,
James Clear
Rights holder, "Atomic Habits"


— — —
NOT LEGAL ADVICE. This template is provided as a starting point for authors who suspect their work was used without permission. For legal counsel specific to your circumstances, consult an intellectual-property attorney. The Authors Guild offers a Legal Services Department to members.
DMCA takedown — Z-Library

To: Z-Library administrators (use the takedown form at z-lib.io / dmca@z-lib.io)

2 June 2026

DMCA Takedown Notice

Pursuant to 17 U.S.C. § 512(c), I formally notify Z-Library and its operators of copyright infringement:

  - Copyrighted work: "Atomic Habits" by James Clear
  - Infringing material location: any Z-Library URL hosting the above work
  - Statement of good faith belief: I have a good faith belief that the use of the material in the manner complained of is not authorised by the copyright owner, its agent, or the law.
  - Accuracy under penalty of perjury: The information in this notice is accurate, and under penalty of perjury, I am the owner, or authorised to act on behalf of the owner, of an exclusive right that is allegedly infringed.

Please remove the infringing material immediately and confirm removal in writing.

James Clear


— — —
NOT LEGAL ADVICE. Standard DMCA template. Z-Library operates outside US jurisdiction; compliance is voluntary but documenting the notice creates an evidentiary record useful in related class actions.
Authors Guild — join the active Meta class action

To: Authors Guild member services (info@authorsguild.org)

Subject: Joining the Meta / LibGen class action

I am writing to confirm my interest in being included as a class member in Kadrey v. Meta and any related class actions arising from Meta's use of LibGen, Z-Library, and PiLiMi to train large language models.

I am a rights holder whose work appears to have been downloaded into Meta's training corpus. Please advise on:

  1. Membership / qualifying steps for the active class
  2. Required documentation to substantiate my claim
  3. Timeline for any settlement distribution

I would also like information about Authors Guild membership and your Legal Services Department.

Thank you,
[YOUR NAME]
[EMAIL]
[POSTAL ADDRESS]

— — —
INFO ONLY, NOT LEGAL ADVICE. The Authors Guild auto-includes US-resident authors whose work was demonstrably scraped — joining the Guild also gives you access to a copyright legal services line at member rates.

Related: audiobook voice cloning

If your book has an audiobook on Audible, Spotify, or YouTube, the narrator’s voice may be cloned by AI voice models. This is a separate rights concern from text scraping — the words are yours, the voice belongs to your narrator. Action: document the narrator’s original consent, register the audiobook with Voice-Cloning Watch (in development), and monitor for unauthorised AI-narrated versions of your book.

Did your publisher already license your book to an AI company?

HarperCollins ↔ Microsoft(Nov 2024) — $5,000 per book licensed for AI training. Author opt-in required; 50/50 author/publisher split. If you’re with HarperCollins, check with your editor — you may have money owed.

Taylor & Francis, Wiley — academic licensing deals. Check via your royalty statement.

Big Four still holding out(Hachette, Penguin Random House, Simon & Schuster, Macmillan) — no public AI licensing deals as of May 2026. Books from these publishers in AI training datasets were NOT licensed; you have stronger claims.

Action plan

Do these, in order.

Sorted by impact. Tick them off as you go.

  1. 01

    Replace your Amazon listing

    Likely lift

    Paste the description, 7 backend keywords, 5 bullets, and bio into KDP.

    30–45 min · 24–48h to re-index

  2. 02

    Pitch the pitchable outlets

    Outreach roulette

    Open the outreach-tiers panel above. Email the green-tagged book blogs / niche listicles that already cite your competitors — they're who AI is reading.

    1–3 hours per outlet · Weeks; depends on editor

Listing rewrite · Amazon

Paste-ready Amazon copy.

Description, bullets, keywords, A+ blocks, bio — generated against your source material. This chapter is Amazon-specific (KDP / Author Central / A+ Content). If your book isn't on Amazon, skip to the next chapter.

  1. 1. Tiny Changes, Remarkable Results
  2. 2. The Practical System for Building Better Habits
  3. 3. Evidence-Based Habit Change for Lasting Results
habit building system for beginnershow to build good habits dailybreaking bad habits for goodsmall changes big results productivitybehaviour change self improvement guidedaily routine improvement strategiesmotivation and discipline practical guide
  • · Discover a proven framework for building good habits and breaking bad ones — designed for anyone who has tried willpower-based approaches and found them unsustainable over the long term.
  • · Works by teaching you to redesign your environment, stack new behaviours onto existing routines, and shift your identity so that lasting change becomes the path of least resistance rather than a constant struggle.
  • · James Clear synthesises research from biology, psychology, and neuroscience into a practical four-step model — cue, craving, response, reward — that explains why habits form and exactly how to reshape them.
  • · Not suited to readers seeking deep academic theory or a single-topic deep-dive into workplace focus or organisational behaviour — those readers may find more targeted coverage in a dedicated cognitive science text.
  • · Walk away with a replicable daily system — not just inspiration — so that small, consistent improvements compound into measurable life change over months and years.

Atomic Habits is for anyone who feels stuck in cycles of failed resolutions and wants a practical, repeatable system — not motivational rhetoric — for making good behaviours stick and bad ones fade. It is especially useful for readers in their twenties through forties who are managing competing demands on their time and need change strategies that work without relying on bursts of willpower. The book is built around a four-stage model of habit formation — cue, craving, response, and reward — and shows readers exactly where to intervene at each stage. Rather than urging you to want things more, it teaches you to make good habits obvious, attractive, easy, and satisfying, while making unwanted habits invisible, unattractive, hard, and unsatisfying. Each principle is paired with concrete techniques you can apply the same day you read the chapter. A central argument running through the book is that identity shapes behaviour more reliably than outcome-focused goals. Instead of saying "I want to run a marathon", the approach asks you to become the kind of person who runs — and to cast small votes for that identity every day. This reframe shifts the psychological foundation of change from external pressure to internal consistency. James Clear draws on findings from psychology, neuroscience, and biology to ground each recommendation, and supplements the research with case studies drawn from elite sport, business, and everyday life. The writing is direct and chapter lengths are short, making the material accessible even in fragmented reading sessions. Readers who already engage deeply with academic behaviour-change literature, or who are specifically looking for extended treatment of workplace deep-focus strategies or the neuroscience of organisational habit loops, may find this book covers familiar ground more briefly than they would prefer. Compared with The Power of Habit, which focuses substantially on the science of habit loops and corporate case studies, Atomic Habits prioritises individual-level, immediately actionable instruction. Compared with Deep Work, which addresses concentrated professional performance, Atomic Habits operates at the level of daily behavioural architecture across all life domains.

Competing titles

AI recommended 10 books instead.

These are who's on the lists you want to be on. Your book is highlighted where it ranks (or at the bottom if it didn't rank).

Run integrity

8 of 11 audit components completed.

Every audit on this product runs the same set of components. This panel records which actually ran for your report so you can confirm nothing was silently skipped.

Now

Ship it.

Then re-audit in 4–6 weeks.

Every re-audit auto-shows the diff vs your last. Score moves, axes shift, listicle outreach lands — you’ll see it.

Download the reportRe-audit later →

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