Integration with Agent Skill

Introduction

The Tianji Data Query Skill is a lightweight, agent-agnostic skill bundle that lets AI agents (Cursor, Claude Code, Codex, Copilot CLI, etc.) query the Tianji platform directly through its read-only OpenAPI.

It follows the agentskills.io specification — a single SKILL.md plus reference files. No long-running process, no extra runtime.

Get started

See the Installation Guide for one-click and manual setup.

What it covers: 69 GET endpoints across 14 service domains:

• Website — traffic stats, pageviews, geo distribution, Lighthouse reports
• Monitor — uptime status, recent check data, monitor events
• Survey — survey responses, result stats, AI categories
• Telemetry — custom event counts, telemetry pageviews, metrics
• Feed — channels, event streams, feed states
• Application — app store reviews, app info, event stats
• Billing / AI Gateway / Worker / Page / Workspace / Global / AuditLog

Skill vs MCP Server

Tianji offers two ways to integrate with AI agents. Pick the one that fits your workflow:

	Agent Skill	MCP Server
Form	Plain documentation files (SKILL.md + references)	A long-running Node.js process
Runtime	None — agent uses curl or built-in HTTP tools	npx tianji-mcp-server
Coverage	69 GET endpoints (read-only, full surface)	A curated subset of tools (read + some write)
Setup	Drop files into the agent's skills directory	Add MCP config to the agent's config file
Best for	Cursor / Claude Code / Codex / any agent following the agentskills.io spec	Agents with first-class MCP support

You can use both at the same time without conflict.

Usage Examples

Once installed, you can ask your AI agent natural-language questions and it will pick the right endpoint:

Example 1: Website traffic overview

User: Show me the pageviews of my main website over the past 7 days.

Agent: [Calls GET /open/workspace/{workspaceId}/website/all to find the site]
       [Then GET /open/workspace/{workspaceId}/website/{websiteId}/pageviews
        with startAt/endAt covering 7 days]
       Your main website received 12,438 pageviews over the past 7 days,
       with a peak of 2,103 on Tuesday. Top referrer: google.com (43%).

Example 2: Monitor health check

User: Are any of my monitors down right now?

Agent: [Calls GET /open/workspace/{workspaceId}/monitor/all]
       [Then GET /open/workspace/{workspaceId}/monitor/{monitorId}/status
        for each monitor]
       2 monitors are currently DOWN:
       - api.example.com (HTTP 503, last UP 12 min ago)
       - db-replica (TCP timeout, last UP 1h ago)
       The other 8 monitors are healthy.

Example 3: Survey result analysis

User: Summarise the responses to the "Q4 Customer Feedback" survey.

Agent: [Calls GET /open/workspace/{workspaceId}/survey/all to resolve the ID]
       [Then GET /open/workspace/{workspaceId}/survey/{surveyId}/stats]
       [Then GET /open/workspace/{workspaceId}/survey/{surveyId}/result/list
        with a pagination cursor]
       "Q4 Customer Feedback" received 218 responses. Average satisfaction
       4.3/5. Top theme: dashboard performance (mentioned 47 times). Most
       requested feature: dark mode (31 mentions).

Sensitive Data Handling

Some endpoints may return platform-stored secrets (e.g. modelApiKey, customModelBaseUrl in AI Gateway responses) or PII (workspace members, audit logs, billing).

The skill instructs agents to:

• Never display apiKey, modelApiKey, secret, token, password, or credential fields.
• Redact or omit these fields when summarising responses.
• For workspace members / audit logs, only surface non-sensitive metadata (names, roles, timestamps) unless the user explicitly requests full detail.

The bundled openapi-readonly.json also pre-redacts these fields at the schema level, so agents cannot accidentally rely on their structure.

Source

The skill source lives in the Tianji repository under skills/tianji-data-query/. Pull requests welcome.