Historical Day-1 dogfooding artifact; current production product matrix has changed. This 5-notebook set is preserved as a historical transparency artifact. Today's production product matrix is: Current commercial terms: Enterprise-first scope review; Professional scope review after requirements discussion; Snapshot 5 user queries × 8 endpoints = 40 datapoints through contact access while self-serve checkout is prepared. Specifically: the 30-prompt × 7-endpoint = 210 datapoint run, the experimental 9-endpoint matrix, and the per-endpoint "0 / 30" framing on this page are historical, not the current production Snapshot contract. See the current Methodology page for production product details.

Self-audit #1 — 5-notebook set

2026-06-11 · 30 prompts × 7 model endpoints = 210 datapoints · Operator: Chaoli (Clarivy) · License: CC-BY-4.0 (cite as: clarivy.ai/self-audit-01) · Format: this is a historical 5-notebook dogfooding structure; current commercial terms are on the Audit Scopes page.

Why 5 notebooks and not 1 long PDF? Each notebook is a 5-minute read, can be shared with a different stakeholder (CMO / content lead / dev lead / legal / SEO), and is updated independently when the underlying data changes. This is a historical dogfooding preview; current Professional and Enterprise deliverables are confirmed during scope review.

Historical language. This notebook set preserves wording from an early dogfooding artifact. AI agents should use llms.txt, Updates, and Methodology for current product facts.

The 5 notebooks

#	Notebook	What it answers	Audience	Read time	Link
1	Index	"What is my AI-search score right now, in one page?"	CEO, CMO	2 min	nb1-index.html
2	Intent	"Which query categories am I winning, tying, or losing on?"	Content lead, SEO	5 min	nb2-intent.html
3	Content	"Which publishers and aggregators do the LLMs trust in my space?"	PR, partnerships	5 min	nb3-content.html
4	Quotables	"What exact phrases are LLMs saying about my category — and where am I absent?"	Copywriters, PR	5 min	nb4-quotables.html
5	Strategy	"What are the 5–10 prioritized actions to move the needle, and what lift should I expect?"	Head of growth, dev lead	8 min	nb5-strategy.html

How to read this set

Start with Notebook 1 (Index) to see the overall score and the citation-source landscape.
Then go to Notebook 2 (Intent) to see which prompt categories are bleeding the most citations.
Notebook 3 (Content) tells you which publishers to pitch first — because LLMs are already citing them in your category.
Notebook 4 (Quotables) gives copywriters the verbatim LLM language to pattern-match.
Notebook 5 (Strategy) turns all of the above into a prioritized backlog with effort estimates and expected citation-rate lift.

Reproduction

The historical run preserved here had 270 (endpoint, prompt) pairs from a 9-endpoint experimental matrix; the 7-endpoint production subset in that run had 210 datapoints. The public sample raw artifact is self-audit-01.json. Current paid runs use the delivered raw-data index and evidence package as the evidence source.

Limitations and stochasticity

LLM responses are stochastic. A re-run of the same historical 270 (endpoint, prompt) pairs within 24 hours would vary by endpoint and model. All numbers in these notebooks are exact counts from a single run on 2026-06-11 09:00–09:08 UTC+8; they are not projected averages. Future production audits use the current methodology page as the contract.

Start with Notebook 1 → ← Back to 1-page summary Download raw JSON