Geolify
Action Center

Every audit ends with a prioritized action list.

Action Center turns GEO audit data into ranked, prescriptive actions - each with Issue, Recommendation, and code-level Example. Ship the highest-impact actions first.

Prioritized Action List
Add llms.txt
HighQuick Win
Fix robots.txt rules
ElevatedHigh Impact
Add JSON-LD schema
HighQuick Win
Why audit-first

Tracking shows where you appear. Auditing tells you why and what to fix.

Most AI visibility tools stop at monitoring - they tell you you’re invisible, but not what to do about it. Action Center turns every audit into a ranked queue of prescriptive actions - each with Issue, Recommendation, and code-level Example. Score, then ship.

Monitoring
Your brand score is 45
Visibility dropped 12%
3 new mentions found
Tells you what happened, not what to do.
Action Center
Issue: Missing llms.txt at root
Recommendation: Publish /llms.txt
Expected effect: +12 GEO Score lift
Tells you what to fix and why it matters.
How it works

From audit to action list to GEO Score lift - in one workflow.

Action Center plugs into every GEO Audit. Each issue becomes a ranked, prescriptive action. Ship the top ones, then re-audit to see your GEO Score move.

Run a GEO Audit

Every audit scans across all 6 GEO pillars and groups findings into 4 action categories - ranked, scoped, ready to ship.

Get a ranked action list

Each finding becomes a prescriptive action - ranked by RICE Impact, tagged with Risk level and timeline. Ship highest-impact actions first.

Track the lift

Re-audit anytime to see GEO Score delta. Prompt Monitor tracks ongoing citation + mention across engines.

Action Center is the bridge between GEO Audit (what’s wrong) and Prompt Monitor (what changed). All three modules share the same brand workspace - no manual hand-off.

Coverage

Every action mapped to one of four categories.

Action Center groups every finding into four action categories - the same four levers AI engines use to decide who gets cited. Each action is ranked by RICE Impact so you ship the highest-ROI work first.

Speed and Performance

Core Web Vitals, TTFB, render-blocking resources. AI crawlers skip slow pages.

Data and Structure

Schema markup, semantic HTML, OpenGraph. Lets AI engines parse what your page means.

Content Quality

E-E-A-T signals, factual depth, citations. AI engines reward content that answers the prompt directly.

Links and Authority

Inbound citations, brand mentions, off-page signals. AI engines weight trusted sources.

RICE Prioritization

Reach × Impact × Confidence ÷ Effort

ImmediateHighElevatedRisingSlow DriftMonitor
Inside a single action

Every action ships with the same six fields.

No vague “improve your content” suggestions. Each action gives your team exactly what to fix, why it matters, and what to expect after shipping.

Speed and Performance
Risk: High
Timeline: 24hRICE: Quick Win

Issue

Your site has no /llms.txt at root. AI agents (GPTBot, ClaudeBot, PerplexityBot) get no curated map.

Recommendation

Publish /llms.txt at site root in markdown (per llmstxt.org). List canonical URLs + one-line description per section. Keep under 500 lines.

Why this matters

Curated ingestion guide leads to fewer parse errors, lower token cost, higher canonical-URL citation chance. GEO-native signal.

Expected effect

AI engines ingest canonical URLs first; noise drops out. First citation lift within 7-14 days of indexing.

Example

# llms.txt - https://example.com
# v1.0 - Last updated: 2026-05-30

# Core sections
/docs/overview: Platform overview and architecture
/docs/api/quickstart: API quickstart guide
/pricing: Pricing and plan comparison

# Featured content
/blog/geo-optimization: GEO optimization guide

References

llmstxt.org · Anthropic Claude crawler docs · OpenAI GPTBot docs

Stop monitoring. Start shipping.

Run a free GEO audit. Get your ranked action list. Ship the highest-impact actions this week.