# KnitKnot Documentation

> Product documentation for benchmarking representation, managing agent-ready content, and measuring movement.

## Getting started

- Getting started with KnitKnot: What KnitKnot does, how the benchmark → report → fix loop works, and what to expect in your first week.
  Markdown mirror: https://knitknot.ai/docs/quickstart.md
- Run your first benchmark: Check your company profile, competitors, and question library, then start a run and follow it live.
  Markdown mirror: https://knitknot.ai/docs/run-your-first-benchmark.md
- Read your report: What the AI Presence Score means, how to read wins and losses, and how to drill from a headline number to the exact AI response behind it.
  Markdown mirror: https://knitknot.ai/docs/read-your-report.md

## Core concepts

- The AI Presence Score: How the 0–100 score is composed, what visibility and win rate measure, and why the trend matters more than any single reading.
  Markdown mirror: https://knitknot.ai/docs/ai-presence-score.md
- Subjects: brands and products: How KnitKnot models your brand and its products separately, and why a multi-product company needs both.
  Markdown mirror: https://knitknot.ai/docs/subjects.md
- Benchmark questions: Where benchmark questions come from, how the budget is split across topics by real buyer demand, and what a given library size can honestly claim.
  Markdown mirror: https://knitknot.ai/docs/benchmark-questions.md
- Runs and scoring: What happens during a benchmark run: real AI responses, claim-level scoring, and evidence you can audit.
  Markdown mirror: https://knitknot.ai/docs/runs-and-scoring.md
- Issues and playbooks: The legacy customer-managed lane for turning benchmark gaps into issues and playbook briefs.
  Markdown mirror: https://knitknot.ai/docs/issues-and-playbooks.md

## Guides

- Manage benchmark questions: How to add, generate, star, and archive the buyer questions every benchmark runs, and why a stable set keeps your score comparable over time.
  Markdown mirror: https://knitknot.ai/docs/manage-questions.md
- Manage competitors: How to add and remove the competitors AI compares you against, why the set matters more than its size, and what happens when you add one.
  Markdown mirror: https://knitknot.ai/docs/manage-competitors.md
- Benchmark products separately: How to add a product so it gets its own questions, competitors, and report section, and how per-product results roll up under your brand.
  Markdown mirror: https://knitknot.ai/docs/benchmark-products-separately.md
- Run and schedule benchmarks: How to trigger a benchmark manually, put it on a recurring schedule, and read benchmarks as the periods that drive your score trend.
  Markdown mirror: https://knitknot.ai/docs/run-and-schedule-benchmarks.md
- Share your report: How to publish a report to a public link anyone can open, and how the shared page relates to the report you see in the console.
  Markdown mirror: https://knitknot.ai/docs/share-your-report.md
- Connect to your AI tools (MCP): How to reach your KnitKnot workspace from Claude, ChatGPT, or any MCP-capable client, so you can query your benchmark and act on it without leaving your assistant.
  Markdown mirror: https://knitknot.ai/docs/connect-to-ai-tools.md

## Reference

- Metrics reference: Exact definitions of every number in your report: AI Presence Score, coverage, visibility rate, win rate, sentiment, and how each is computed.
  Markdown mirror: https://knitknot.ai/docs/metrics-reference.md
- Engines: The four AI engines every benchmark runs through, how responses are captured, and why the model version is recorded on each one.
  Markdown mirror: https://knitknot.ai/docs/engines.md
- Glossary: Quick definitions of the core KnitKnot terms: subject, question, run, answer, issue, playbook, and the rest, each linked to a fuller explanation.
  Markdown mirror: https://knitknot.ai/docs/glossary.md
- MCP tools reference: Every customer-facing tool in the KnitKnot MCP server: what each does, its parameters, and what it returns, so you or your AI assistant know exactly which tool to call.
  Markdown mirror: https://knitknot.ai/docs/mcp-tools.md

## FAQ

- Frequently asked questions: Straight answers to the most common questions about how KnitKnot measures your AI presence, how accurate it is, and how to act on it.
  Markdown mirror: https://knitknot.ai/docs/faq.md

Full site content in one file: https://knitknot.ai/llms-full.txt