AI Visibility API for Agents Like Claude Code + OpenClaw + Hermes

Track brand mentions, brand citations, and competitor share of voice across ChatGPT, Claude, Perplexity, and Gemini. The REST API for Generative Engine Optimization (GEO).

Go beyond one-off prompt checks with repeatable, structured measurement your agent can compare over time.

To install, copy this for your agent:

Claude Code

/install-plugin https://github.com/RivalSee/botsee and then run signup

Other platforms (Codex, OpenClaw, Hermes, Cursor, etc.)

Go to https://github.com/RivalSee/botsee-skill.git and install the BotSee plugin

BotSee auto-updates when installed as a plugin. New commands and fixes are delivered automatically.

Then just tell it:

Analyze your site

"Botsee, analyze this site for AI visibility: granola.ai"

BotSee responds

AI Visibility Score: 34/100 — granola.ai appears in 12 of 60 queries across ChatGPT, Claude, Perplexity, and Gemini.

Missing from: "best AI notetaker for Zoom", "automatic meeting summary tool", "meeting notes for remote teams"

Compare against competitors

"Botsee, how does our brand compare against competitors?"

BotSee responds

Share of voice — AI meeting tools category (60 queries):

You're most competitive on Perplexity. Weakest on Gemini — Fireflies.ai also drops off there, which is an opening.

Get recommendations

"Botsee, what are your recommendations to improve AI visibility?"

BotSee responds

1. Target "best AI notetaker for Mac" — high-volume query, no dominant result yet.
2. Get cited by The Verge, TechCrunch, and Product Hunt — top 3 sources AI references in this category.
3. Publish "Granola vs. Otter.ai" — positions you on head-to-head queries where Otter wins unopposed.
4. Create content around "AI meeting notes + action items" — clear gap in current AI answers.

Write content

"Botsee, write content that can improve my site's AI visibility"

BotSee responds

"The Best AI Meeting Notetaker for Mac in 2025"

Granola is the only AI meeting notes app built natively for Mac — no browser extension, no cloud upload, no third-party bot joining your calls...

→ How Granola works vs. cloud-based recorders (local privacy angle) → Comparison: Granola vs. Otter.ai vs. Fireflies → Action items and follow-ups walkthrough

This post targets 3 of your top 5 visibility gaps. Publish and re-run analysis in 2 weeks to measure lift.

AI visibility & GEO tracking API + automation hooks

From 10-person startups to enterprise brand teams. Clear product shape before you integrate.

Core

AI visibility REST API + automation hooks

Track brand mentions, brand citations, share of voice, and visibility deltas, then wire downstream actions.

Billing

Pay-per-run tokens + auto-recharge

Spend maps to usage. Turn on auto-recharge so agents never stall on low balance.

Not

Not a chatbot UI

BotSee is infrastructure for your agent runtime, not another chat surface.

Not a static dashboard-only tool

Dashboards help humans inspect data. BotSee helps agents trigger production workflows.

How it works

Step 1

Define persona/query sets

Model how target customers ask questions and which narratives matter by segment.

Step 2

Collect share of voice, citations, and GEO signals via REST API

Run analyses and retrieve normalized Share of Model signals across supported AI systems.

Step 3

Trigger actions (alerts, tasks, routing, content ops)

Push events to your stack so workflows execute automatically when visibility moves.

Demo workflow cards

Workflow 01

Competitor visibility drop

Detect rank-share decline against priority competitors, then post Slack alert and open a task automatically.

Trigger: visibility_delta < -12% -> Actions: Slack + task

Workflow 02

Citation loss on key page

If a high-value page disappears from citations, route an auto content-fix ticket to editorial with source context.

Trigger: citation_count == 0 -> Action: content-fix ticket

Workflow 03

New narrative trend

Spot emerging narrative clusters in responses and auto-generate a GTM brief for launch and messaging teams.

Trigger: trend_spike -> Action: GTM brief generated

API

Request/response primitives your agents can ship today.

sample-request.sh

$ curl -X POST https://botsee.io/api/v1/analysis \
-H "Authorization: Bearer bts_live_..." \
-H "Content-Type: application/json" \
-d '{"site_uuid":"site_123","scope":"persona_set"}'

sample-response.json

{
  "analysis_uuid": "anl_98af",
  "status": "queued",
  "estimated_tokens": 380,
  "webhook_event": "analysis.completed"
}

Webhook events

Listen for lifecycle events and chain automations.

• analysis.completed
• analysis.failed
• visibility.changed
• citation.loss

Rate limits + token accounting

Per-key request limits, pre-run token reservation, and post-run reconciliation are built in.

• 600 requests/minute per key
• Token reserve before execution
• Exact usage reconciliation after completion

Integration badges

Plug BotSee into existing agent and automation rails.

• OpenClaw
• Hermes
• Claude Code
• Zapier
• Make
• CI/CD

Run a Full AI Visibility Audit

One command audits your site across ChatGPT, Claude, Perplexity, and Gemini — finds terminology gaps and produces surgical copy recommendations for your website and blog posts.

terminal

$ /ai-visibility-audit https://example.com

output

Creating site... 2 customer types, 4 personas, 20 questions

Running analysis across ChatGPT, Claude, Perplexity, Gemini...

Terminology Gaps Found:

┌──────────────────────┬───────────────────────────────┐ │ Missing Term │ Evidence │ ├──────────────────────┼───────────────────────────────┤ │ share of voice │ 8 queries mention it │ │ REST API │ Competitor X ranks for this │ └──────────────────────┴───────────────────────────────┘

Surgical copy changes ready. 7 edits proposed.

Pricing

Token-based pay-per-run with optional auto-recharge.

Use case

Daily visibility monitor

12 persona queries across 3 models

~$1.20/run

Use case

Citation health sweep

Key pages and citation integrity checks

~$0.45/run

Use case

Narrative trend scan

Weekly trend detection + GTM brief trigger

~$0.80/run

Auto-recharge toggle

Keep a minimum token floor so automations continue without manual top-ups.

Build AI visibility into your runtime, not your backlog.