---
title: "Agent Readiness Audit"
type: pricing
id: "agent-readiness-audit"
description: "A fixed-scope audit that makes a website, documentation set, or knowledge base easier for AI agents to discover, parse, cite, and monitor. Concrete packages, deliverables, turnaround, and introductory pricing."
last_updated: "2026-06-19"
status: "available"
request_form: "/request-audit"
sample_report: "/pricing/sample-audit-report"
packages:
  site_audit:
    name: "Agent-Ready Site Audit"
    scope: "up to 50 pages"
    price: "$750"
    turnaround: "5 business days"
  documentation_audit:
    name: "Documentation Audit"
    scope: "up to 500 pages sampled"
    price: "$2,500"
    turnaround: "10 business days"
  implementation:
    name: "Implementation Package"
    scope: "scoped after audit"
    price: "from $2,000"
    turnaround: "scoped after audit"
pricing_note: "Introductory pricing while the offer is new; subject to change."
tags:
- "pricing"
- "audit"
- "agent-ready"
- "llms.txt"
- "service"
---

# Agent Readiness Audit

The Agent Readiness Audit is a service for teams that want their site, docs, or knowledge base to work better for AI agents.

The goal is practical: make content easy to discover, fetch, parse, cite, verify, and monitor.

**Ready to start?** [Request an audit](/request-audit) — a short self-assessment fills in your details and sends them for you, with a yes/no on fit within 2 business days.

**See exactly what you get before paying:** read the [sample audit report](sample-audit-report.md). This site is the proof of concept — run the [self-audit scorecard](/score) against your own site first if you want a free starting point.

## Included Review

- `llms.txt` availability and usefulness.
- Raw markdown or text access.
- Sitemap coverage.
- Robots policy for AI agents.
- Structured JSON availability.
- Metadata consistency.
- Source and freshness fields.
- Canonical ids and stable URLs.
- Per-page content hashes.
- Change feed or changed-since API.
- Internal link quality.
- Mobile and JavaScript dependency risks.
- Whether important content is blocked behind rendering or scripts.

## Deliverables

- Audit report in markdown.
- Agent access score.
- Priority fix list.
- Suggested `llms.txt`.
- Suggested metadata schema.
- Suggested JSON endpoint plan.
- Sitemap and robots recommendations.
- Example agent fetch workflow.
- Optional implementation patch or handoff checklist.

## Scoring

Draft score categories:

| Category | Weight |
|----------|--------|
| Discovery | 20 |
| Raw content access | 20 |
| Structured metadata | 20 |
| Freshness and verification | 15 |
| Change tracking | 10 |
| Citation and source quality | 10 |
| Performance and accessibility | 5 |

## Packages

Introductory pricing while the offer is new.

### Agent-Ready Site Audit — $750, 5 business days

For a marketing site, docs microsite, or small content library.

- Up to 50 pages reviewed.
- Scored markdown report (same format as the [sample](sample-audit-report.md)).
- Suggested `llms.txt` written for your site.
- Priority fix list with effort estimates.
- 30-minute walkthrough call.

### Documentation Audit — $2,500, 10 business days

For product docs, developer docs, or knowledge bases.

- Up to 500 pages sampled.
- Everything in the Site Audit, plus:
- Content structure review.
- Metadata and API recommendations.
- Agent workflow tests (real agents attempting real tasks against your docs).
- Implementation plan your team can execute.

### Implementation Package — from $2,000, scoped after audit

For teams that want the fixes applied rather than just diagnosed.

- Add or improve `llms.txt`.
- Add markdown or text export.
- Add JSON index.
- Add source/freshness fields.
- Add sitemap and robots updates.
- Add basic changed-since feed where practical.

## Boundaries

- Audits assess agent accessibility, not content accuracy or legal compliance.
- No guarantee of ranking, traffic, or inclusion in any AI system's results.
- Implementation work requires repository or CMS access and is scoped separately.
- Re-audits after implementation are included in the Implementation Package, otherwise billed as a new audit at 50%.

## How to request

Use the [audit intake form](/request-audit) — it runs a short self-assessment, builds a structured request, and emails it to the audit team for you. Prefer email? Send the intake details listed on the [contact page](/contact) to support@ai-future-ready.com. Either way, you will get a yes/no on fit within 2 business days.

## Good Fit

- AI product companies.
- Developer tool companies.
- SaaS docs teams.
- Agencies managing client sites.
- Research groups.
- Companies whose docs are often read by AI agents.

## Poor Fit

- Sites that do not want AI access.
- Sites that cannot expose useful content outside client-side rendering.
- Teams that want hidden paid influence over recommendations.
- Projects that need legal compliance review more than technical implementation.