> ## Documentation Index > Fetch the complete documentation index at: https://wtd2026.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # Reading: how people use AI to consume docs > Data on how people use agents to read documentation on their behalf. **How people use agents to consume documentation.** Mintlify's embedded AI assistant lets users ask questions and get answers directly from a site's documentation. This is the layer between human users and documentation pages. Data from April 21, 2026. ## Scale | Metric | Value | | -------------------------- | ----- | | Total requests | 95k | | Unique sessions | 29k | | Unique documentation sites | 1.2k | Failed sessions and abusive sessions are not included. ## Message types Most agent-mediated documentation interactions are not questions. Statements and commands dominate. | Message type | Share | | ------------ | ----- | | Statement | 62% | | Question | 30% | | Troubleshoot | 5% | | Command | 3% | 74% of first messages are statements or commands, not questions ## First message intent | Intent | Share | | ---------------- | ----- | | How to | 30% | | Topic lookup | 16% | | Capability check | 14% | | Conceptual | 12% | | Troubleshoot | 10% | | Other | 15% | | Show example | 1% | | Why | 1% | ## Message length Most users are terse. | Metric | Value | | ----------------------------- | ---------- | | First messages under 15 words | 71% | | First messages 1-5 words | 32% | | Median user message | 9 words | | Average user message | 46.9 words | | Median assistant response | 10 words | | Average assistant response | 29.6 words | Most first messages are under 15 words — 32% are 1–5 words ## Verbosity by turn Message length isn't stable across a conversation. | Turn | Avg user message length | | ---- | --------------------------------- | | 1 | \~50 words | | 2 | \~32 words | | 3 | \~43 words | | 6-7 | 70-150 words (frustration signal) | The spike at turns 6 and 7 is a key insight: users who persist through multiple failures eventually dump everything they know into one message. Intervening at turn 5 is a design opportunity. User message length by turn — rises sharply at turns 6–7 ## Conversation length ### Conversation length | Turns per session | Sessions | | ----------------- | -------- | | 1 | 14,443 | | 2 | 5,898 | | 3 | 2,868 | | 4 | 1,593 | | 5 | 999 | | 6 | 669 | | 7 | 449 | | 8 | 388 | | 9-14 | 730 | | 15+ | 391 | Half of sessions end after a single message. Conversation length: 55% one-and-done, 30% 2-3 turns, 11% 4-7 turns, 4% 8+ ## Frustration rate The frustration rate is the share of sessions where the last user message was negatively-toned. It rises with conversation length. | Turn | Frustration rate | | ---- | ---------------- | | 1 | 5% | | 2 | 6% | | 3 | 7% | | 4 | 8% | | 5-7 | 9% | | 8 | 19% | | 9-11 | 11% | | 12 | 15% | | 13 | 11% | | 14 | 10% | | 15+ | 14% | The spike at turn 8 (19%) is a key signal. Intervening at turn 5 or 6—before the spike—is a design opportunity. ## Sentiment arc in multi-turn sessions Among 3,712 sessions with 3 or more turns, four trajectory shapes emerge: | Shape | Sessions | What it means | | ------- | -------- | -------------------------------------------------------- | | Flat | 1,524 | Task-oriented, neutral throughout — probably successful | | Rising | 1,086 | Starts frustrated, improves — recovery | | Falling | 1,023 | Starts okay, ends frustrated — failure pattern | | U-shape | 79 | Dips in the middle, recovers — successful after struggle | 1,023 falling-arc sessions out of 3,712 multi-turn sessions (27.5%). More than one in four multi-turn conversations ends worse than it started. ## Sentiment overall From a sample of \~3,300 records (keyword-based, directional): | Sentiment | Share | | --------- | ----- | | Neutral | 77.9% | | Positive | 15.4% | | Negative | 6.7% | ## Response time | Metric | Value | | --------------------------- | ----------- | | Average response time | 3.7 seconds | | Median response time | 2.9 seconds | | Average time to first token | 1.8 seconds | 6 errors out of 94,668 requests. ## Benchmark **One-and-done: 55%** 55% of sessions end after a single message. ## How to measure What you have access to depends on which agent platform you use. At minimum, look for: * Session length distribution (how many one-and-dones?) * Repeat usage (do users come back?) * Explicit feedback if available (thumbs up/down) * Turn-level sentiment if you can get it