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WireLog WireLog

Agents

View as markdown

Dashboards are for humans. Agents cannot click buttons, read charts, or navigate UIs. They need structured text they can parse, reason over, and act on.

WireLog returns Markdown tables from queries. Every analytics result is text an agent can consume directly.

Two integration paths

1. Claude Code Skills

SKILL.md files teach coding agents the WireLog DSL, instrumentation patterns, and project setup. The agent reads the skill on activation and gains domain knowledge — no tool registration required.

Three skills: wirelog (query), wirelog-instrument (add tracking to code), wirelog-setup (new project setup).

2. Direct HTTP

Any agent can POST /query and get Markdown back:

Terminal window
curl -X POST https://api.wirelog.ai/query \
  -H "X-API-Key: sk_YOUR_SECRET_KEY" \
  -H "Content-Type: application/json" \
  -d '{"q": "* | last 7d | count by event_type | top 10"}'

Returns a Markdown table. No SDK, no client library, no dependencies.

The agent workflow

1. Discover events
   -> wirelog_list_events (or: * | last 30d | count by event_type | top 20)


2. Write a query
   -> signup | last 30d | count by day


3. Read the Markdown table
   -> | day        | count |
      |------------|-------|
      | 2026-02-01 |    42 |
      | 2026-02-02 |    38 |


4. Reason over the data
   -> "Signups dropped 10% day-over-day"


5. Act
   -> Investigate, alert, recommend, or fix

If discovery shows mostly page_view (script-tag-only data), pivot to page-view-first analysis:

page_view | last 7d | count by day
page_view | last 30d | count by _path | top 20
page_view | where _path in ["/","/pricing","/docs"] | last 7d | count
paths from page_view | last 30d | by _path
sessions | last 30d | count by session.utm_source

Example: agent-driven funnel analysis

An agent investigating signup conversion:

Step 1: Discover events
  Query: * | last 30d | count by event_type | top 20
  Result: signup (1200), activate (800), purchase (200), page_view (15000), ...


Step 2: Build funnel
  Query: funnel signup -> activate -> purchase | last 30d
  Result: signup 1200 -> activate 800 (66.7%) -> purchase 200 (25.0%)


Step 3: Break down by platform
  Query: funnel signup -> activate -> purchase | last 30d | by _platform
  Result: web: 60% activation, mobile: 45% activation


Step 4: Reason
  "Mobile activation is 15pp below web. The mobile onboarding flow
   needs investigation."


Step 5: Recommend
  "Add mobile-specific onboarding steps. Track mobile_onboarding_step
   events for granular funnel visibility."

Next steps